Patent Publication Number: US-2023162380-A1

Title: Mitigation of registration data oversampling

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This patent document claims priority to and the benefit of U.S. Provisional Patent Application No. 63/001,169, titled “MITIGATION OF REGISTRATION DATA OVERSAMPLING” and filed on Mar. 27, 2020. The entire content of the aforementioned patent application is incorporated herein by reference as part of the disclosure of this patent document. 
    
    
     TECHNICAL FIELD 
     The present disclosure is directed to systems, devices, methods, and computer program products for registering instrument and image frames of reference. 
     BACKGROUND 
     Minimally invasive medical techniques are intended to reduce the amount of tissue that is damaged during medical procedures, thereby reducing patient recovery time, discomfort, and harmful side effects. Such minimally invasive techniques may be performed through natural orifices in a patient anatomy or through one or more surgical incisions. Through these natural orifices or incisions, an operator may insert minimally invasive medical tools to reach a target tissue location. Minimally invasive medical tools include instruments such as therapeutic, diagnostic, biopsy, and surgical instruments. Medical tools may be inserted into anatomic passageways and navigated toward a region of interest within a patient anatomy. Navigation may be assisted using images of the anatomic passageways. Improved systems and methods are needed to accurately perform registrations between medical tools and images of the anatomic passageways. 
     SUMMARY 
     Disclosed are devices, systems, methods, and computer program products for mitigating oversampling of data points collected by a medical device when steered to particular regions of an anatomic structure for surveying the anatomic structure, such as airways in regions of the lungs and bronchial tubes, e.g., in advance of a medical procedure. 
     In some embodiments, for example, a system for mitigating oversampling of data points includes a medical device comprising a sensor, wherein the medical device is insertable in an anatomic passageway of a patient such that the sensor is operable to detect one or both of a position and a motion of the medical device when inserted in the anatomic passageway; and a computing device in communication with the medical device, the computing device comprising a processor, and a memory coupled to the processor and storing instructions that, when executed by the processor, cause the system to perform operations comprising: receiving data points detected by the sensor of the medical device, the received data points associated with one or both of the detected position and the detected motion of the medical device; analyzing a set of the received data points to determine a motion parameter associated with a movement or change in position of the sensor of the medical device in a region of the anatomic passageway, wherein the motion parameter includes a change of one or both of a translational motion and a rotational motion of the sensor; comparing the motion parameter to a threshold to determine whether to accept the set of data points when the motion parameter satisfies the threshold or to reject the set of data points when the motion parameter does not satisfy the threshold; and recording the accepted set of data points in a survey point cloud usable to register the medical device in an anatomic frame of reference space. 
     In some embodiments, for example, a system for mitigating oversampling of data points includes a medical device comprising a sensor, wherein the medical device is insertable in an anatomic passageway of a patient such that the sensor is operable to detect one or both of a position and a motion of the medical device when inserted in the anatomic passageway; and a computing device in communication with the medical device, the computing device comprising a processor, and a memory coupled to the processor and storing instructions that, when executed by the processor, cause the system to perform operations comprising: receiving data points detected by the sensor of the medical device, the received data points associated with a detected position of the medical device; analyzing the received data points to determine a distance parameter associated with a distance between a data point and one or more nearest neighbors of the data point; comparing the distance parameter to a threshold to determine whether to accept the data point among the received data points when the distance parameter satisfies the threshold or to reject the data point among the received data points when the distance parameter does not satisfy the threshold; and recording accepted data points in a survey point cloud usable to register the medical device in an anatomic frame of reference space. 
     In some embodiments, for example, a system for mitigating oversampling of data points includes a medical device comprising a sensor, wherein the medical device is insertable in an anatomic passageway of a patient such that the sensor is operable to detect one or both of a position and a motion of the medical device when inserted in the anatomic passageway; and a computing device in communication with the medical device, the computing device comprising a processor, and a memory coupled to the processor and storing instructions that, when executed by the processor, cause the system to perform operations comprising: receiving data points detected by the sensor of the medical device, the received data points associated with a detected position of the medical device; analyzing the received data points to determine a density parameter associated with a density of one or more data points to nearest neighbors data points; comparing the density parameter to a threshold to determine whether to accept the one or more data points among the analyzed data points when the density parameter satisfies the threshold or to reject the one more data points when the density parameter does not satisfy the threshold; and recording accepted data points in a survey point cloud usable to register the medical device in an anatomic frame of reference space. 
     In some embodiments, for example, a system for mitigating oversampling of data points includes a medical device comprising a sensor, wherein the medical device is insertable in an anatomic passageway of a patient such that the sensor is operable to detect one or both of a position and a motion of the medical device when inserted in the anatomic passageway; and a computing device in communication with the medical device, the computing device comprising a processor, and a memory coupled to the processor and storing instructions that, when executed by the processor, cause the system to perform operations comprising: receiving data points detected by the sensor of the medical device, the received data points associated with a detected position of the medical device; analyzing the received data points to determine a density parameter associated with a density of one or more data points to nearest neighbors data points; comparing the density parameter to a threshold to determine whether to alter a weighting value of the one or more data points within the analyzed data points; when the density parameter meets the threshold, altering the weighting value of the one or more data points; and recording the data points to register the medical device in an anatomic frame of reference space. 
     It is to be understood that both the foregoing general description and the following details description are exemplary and explanatory in nature and are intended to provide an understanding of the present disclosure without limiting the scope of the present disclosure. In that regard, additional aspects, features, and advantages of the present disclosure will be apparent to one skilled in the art from the following detailed description. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Many aspects of the present disclosure can be better understood with reference to the following drawings. The components in the drawings are not necessarily to scale. Instead, emphasis is placed on illustrating clearly the principles of the present disclosure. The drawings should not be taken to limit the disclosure to the specific embodiments depicted, but are for explanation and understanding only. 
         FIG.  1    shows a diagram illustrating a method for mitigating oversampling of data points in accordance with various embodiments of the present technology. 
         FIG.  2    shows a diagram illustrating an example motion collection-based method for mitigating oversampled data in accordance with various embodiments of the method of  FIG.  1   . 
         FIG.  3 A  shows a diagram illustrating an example point distance rejection-based method for mitigating oversampled data in accordance with various embodiments of the method of  FIG.  1   . 
         FIG.  4 A  shows a diagram illustrating an example point density rejection-based method for mitigating oversampled data in accordance with various embodiments of the method of  FIG.  1   . 
         FIG.  5    shows a diagram illustrating a survey density normalization-based method for mitigating oversampled data in accordance with various embodiments of the method of  FIG.  1   . 
         FIG.  6    shows a schematic diagram of a robotic or teleoperated medical system configured in accordance with various embodiments of the present technology. 
         FIG.  7    shows a schematic diagram of a manipulator assembly, a medical instrument system, and an imaging system configured in accordance with various embodiments of the present technology. 
         FIG.  8    shows an illustrative diagram of a portion of the medical instrument system of  FIG.  7    extended within an anatomic region of a patient in accordance with various embodiments of the present technology. 
         FIG.  9    shows a diagram illustrating a plurality of coordinate points that form a point cloud representing a shape of the portion of the medical instrument system of  FIG.  8    extended within the anatomic region shown in  FIG.  8   . 
         FIG.  10    shows a diagram illustrating a navigation image of real patient anatomy from a viewpoint of the portion of the medical instrument system of  FIG.  8    extended within the anatomic region shown in  FIG.  8   . 
         FIG.  11    shows a diagram illustrating an intra-operative image of a portion of the anatomic region of  FIG.  8    while the portion of the medical instrument system of  FIG.  8    is extended within the anatomic region. 
         FIG.  12    shows a diagram of a display system displaying a composite virtual navigational image in which the medical instrument system of  FIGS.  7  and  8    is registered to an anatomic model of the anatomic region of  FIG.  8   , a virtual navigational image of the virtual patient anatomy, and a real navigational image of the real patient anatomy within the anatomic region in accordance with various embodiments of the present technology. 
     
    
    
     DETAILED DESCRIPTION 
     The system and techniques disclosed herein may be used to register a medical instrument reference frame to an image frame of reference for an intra-operative anatomic image that includes an image of the medical instrument, such as a catheter. Often, anatomical motion can result in intra-operative images that are too distorted to clearly isolate and segment the catheter and in medical instrument position data that is agitated. By representing the intra-operative image of the medical instrument as a cloud of points (also referred to as a “image point cloud”) and the shape of the medical instrument (obtained by a sensor during the image capture period) as a cloud of points (also referred to as a “sensor point cloud”), point matching registration techniques, such as an iterative closest point (ICP) technique, can be used to register the sensor point cloud and the image point cloud. The robustness of this registration technique allows the image frame of reference to be registered to the medical instrument frame of reference, despite data spread caused by patient anatomical motion. 
     Specific details associated with several embodiments of the present technology are described herein, some with reference to  FIGS.  1 - 12   . Although some of the embodiments are described with respect to particular medical systems and devices in the context of navigating and performing medical procedures within lungs of a patient, other applications and other medical system and medical device embodiments in addition to or alternative to those described herein are within the scope of the present technology. For example, unless otherwise specified or made clear from context, the devices, systems, methods, and computer program products of the present technology can be used for various image-guided medical procedures, such as medical procedures performed on, in, or adjacent hollow patient anatomy, and, more specifically, in procedures for surveying, biopsying, ablating, or otherwise treating tissue within and/or proximal the hollow patient anatomy. Thus, for example, the systems, devices, methods, and computer program products of the present disclosure can be used in one or more medical procedures associated with other patient anatomy, such as the bladder, urinary tract, and/or heart of a patient. 
     It should be noted that other embodiments in addition to those disclosed herein are within the scope of the present technology. Further, embodiments of the present technology can have different configurations, components, and/or procedures than those shown or described herein. Moreover, a person of ordinary skill in the art will understand that embodiments of the present technology can have configurations, components, and/or procedures in addition to those shown or described herein and that these and other embodiments can be without several of the configurations, components, and/or procedures shown or described herein without deviating from the present technology. 
     As used herein, the term “physician” shall be understood to include any type of medical personnel who may be performing or assisting a medical procedure and, thus, is inclusive of a doctor, a nurse, a medical technician, other similar personnel, and any combination thereof. Additionally, or alternatively, as used herein, the term “medical procedure” shall be understood to include any manner and form of diagnosis, treatment, or both, inclusive of any preparation activities associated with such diagnosis, treatment, or both. Thus, for example, the term “medical procedure” shall be understood to be inclusive of any manner and form of movement or positioning of a medical device in an anatomical chamber. As used herein, the term “patient” should be considered to include human and/or non-human (e.g., animal) patients upon which a medical procedure is being performed. 
     Example Embodiments of Techniques for Mitigating Oversampling of Registration Data 
     Point matching registration techniques, like ICP technique, used to register collected data points in a point cloud are generally robust, in that, implementations of such techniques can provide reliable registration data for establishing a frame of reference to track a medical instrument relative to the patient&#39;s anatomy within which it is inserted. However, any point matching technique, including ICP, are susceptible to some degree of error as a result of inaccuracy in the collected point sets. This is due to misalignments between the real anatomical structure of the patient&#39;s anatomy and a model of the anatomical structure that are inherent. Commonly, this error is the result of physical deformation (e.g., patient breathing, motion, shifting) relative to the previously-acquired model of the patient anatomy, e.g., created from previously-acquired data such as in a pre-operation image of the patient&#39;s anatomy to produce an initial model of the anatomical structure. This variability in physical deformation can result in variabilities in the level of misalignment in different parts of the anatomical structure. In general, an optimal registration is considered that which minimizes the misalignment between real and model-based reference frames. 
     Registration techniques such as ICP can mathematically compute this optimal alignment by minimizing the error between collected and model-based point sets. However, because ICP is susceptible to inherent physiological misalignments, the resulting error can be made worse by sampling processes that magnify or give more weight to some data over others. Such sampling processes can be affected by the way a medical instrument is manipulated to collect or sample point data from various regions. One example of worsening the error in point matching registration is “overdriving” of the insertable medical instrument where a sensor associated with the insertable medical instrument is used to disproportionally survey an area or areas of the patient&#39;s anatomy as compared to other areas. Overdriving results in the oversampling and over-representation of points for the over-surveyed areas, which causes undue weighting of the data points in the point matching registration process. 
     As an example, some medical systems may implement a registration protocol that requires the system user to position the sensor (e.g., associated with the system&#39;s insertable medical device) in a plurality of anatomic regions. The registration protocol facilitates the collection of data points for a point cloud to be registered with a global data set (e.g., created from a pre-procedural image), referred to as “survey data.” For example, the registration protocol may request or require the system user to move the medical device with the associated sensor device to a first area of the anatomic structure (e.g., determined from the pre-procedural image), to a second area, to a third area, and so forth. However, the medical system may have little to no control on where, when or how the system user “drives” the medical device with the associated sensor device during the registration protocol, which makes the registration prone to oversampling data in regions of the anatomic structure where the user may “overdrive” the device more frequently with respect to other regions of interest. This may cause inaccuracies in the registration of survey data with the global data set. 
     One way to deal with this issue is to not collect any survey data when the medical device is stationary and only collect data when the medical device is in motion relative to the anatomic structure. However, this technique is insufficient as data would still be oversampled when the device is moved repetitively by the user in a given area of the anatomic structure. What is needed is an effective and convenient (e.g., non-taxing of computing resources) way to mitigate oversampling of survey data when a medical device performs registration. 
     In some embodiments in accordance with the present technology, a computer-implemented method for mitigating oversampling of data points collected by a sensor associated with a medical device includes analyzing (i) parameter(s) of the sensor (of the medical device) and (ii) parameter(s) of the sampled data points, and, in real-time, comparing one or both of the analyzed sensor parameter(s) and/or data point parameter(s) to a threshold value, respectively, where individual data points among the sampled data points are recorded in a registration point cloud when the respective parameter(s) satisfies the threshold. An example embodiment of such a method is described in connection with  FIG.  1   . 
       FIG.  1   , for example, is a flow diagram illustrating a method  1000  for mitigating oversampling of data points in accordance with various embodiments of the present technology. Various embodiments of the method  1000  can be based on a point sampling technique to mitigate oversampling and/or on a density normalization technique to mitigate oversampling. All or a subset of the steps of the method  1000  can be implemented by a computing device, such as a control system of a medical system or device, including various components or devices of a robotic or teleoperated system. The method  1000  includes a set of operations or processes  1010 - 1040 . 
     The computing device for implementing the method  1000  includes one or more processors coupled to one or more memory devices storing instructions that, when executed by the one or more processors, cause the computing device to perform operations in accordance with the processes  1010 - 1040 . In some implementations where the computing device is included in a robotic or teleoperated medical system, the computing device is in data communication with a medical instrument system, which includes the medical device and the sensor, and receives sensor data for mitigating oversampling of data points. The sensor is configured to generate position sensor data and/or motion sensor data during a registration protocol where the medical device is driven in an anatomical structure or structures of the patient (e.g., driven through anatomic passageway(s) of the patient). In this manner, the position sensor data is associated with one or more positions of the medical device within the anatomic passageway, and the motion sensor data is associated with the translational motion and/or the rotational motion of the medical device within the anatomic passageway. Optionally, in some embodiments, the medical instrument system includes an image capture device configured to capture image data of patient anatomy within the anatomic passageway during the data sampling of the anatomic structure(s). The method  1000  is described below with reference to an exemplary robotic or teleoperated medical system  100  (“medical system  100 ”), discussed later in connection with  FIGS.  6  and  7   . 
     At process  1010 , the method  1000  receives, at the computing device, data points that correspond to a sampled survey point cloud detected by a sensor of a medical device (e.g., the shape sensor  233  and/or of the position measuring device  239  of the medical instrument system  204  shown in  FIGS.  6  and  7   ) during data sampling by the sensor of an anatomic structure or structures of a patient. The received data points at the computing device can be associated with a position and/or a motion of the sensor, e.g., thereby of the medical device. 
     At process  1020 , the method  1000  determines, at the computing device, a first parameter associated with the medical device (e.g., the sensor and/or other component of the medical device) and/or a second parameter associated with the received data points. In some implementations of the process  1020 , the first parameter includes a motion parameter associated with the medical device. In such implementations, determining the first parameter can include determining a change of the translational motion and/or rotational motion of the medical device, such as a change in a roll value or a pitch value and/or a yaw value of the sensor of the medical device (e.g., such as the medical instrument system  204 , at the tip of the shape sensor  233 ). In some implementations of the process  1020 , the second parameter can include a point distance parameter and/or a point density parameter associated with the received data points. In such implementations, determining the second parameter can include determining (i) a distance from a data point to its nearest neighbor within the sampled survey point cloud, and/or (ii) a density of the data points, e.g., within a predefined subset of the sampled survey point cloud corresponding to a sub-region of the anatomic structure. One, some or all of the above example features may be implemented by the process  1020 . 
     At process  1030 , the method  1000  analyzes, at the computing device, the first parameter and/or the second parameter by comparing the first parameter to a first threshold  and/or by comparing the second parameter to a second threshold, respectively. For example, the first threshold and second threshold can each include a threshold value or range of values. As an example, the first threshold value or range of values can include a velocity (or velocity range) that the sensor exhibited by movement from the previous sample. As another example, the second threshold value or range of values can include a minimum distance or distance range that the sensor was translated or rotated from the previous sample, e.g., the previous sample taken temporally. In some implementations of the process  1030 , where the second parameter includes a determined distance from a data point to its nearest neighbor within the sampled survey point cloud, the determined distance can be compared to a distance threshold. In some implementations of the process  1030 , where the second parameter includes a determined density value of data points, the determined density value can be compared to a density threshold. One, some or all of the above example features may be implemented by the process  1030 . 
     At process  1040 , the method  1000  records, at the computing device, an individual data point (among the received data points) in a registration point cloud when the first parameter and/or the second parameter satisfies the respective threshold. In this manner, for example, the identified individual data point(s) from the received data points can be added to the recorded coordinate points that form positional point cloud data representing a shape of the medical device within an anatomic region. In some implementations of the process  1040 , the received data points are initially recorded in the registration point cloud, after which the process  1040  rejects any individual data point when the determined second parameter satisfies the threshold value. Yet, in some implementations of the process  1040 , the process  1040  includes only adding an individual data point when the determined second parameter satisfies the threshold value. Yet, in some implementations, prior to recording the individual data points, the process  1040  can be implemented to decrease a weighting value of a data point when the determined density of data points (as the second parameter) exceeds a threshold density. 
     In some embodiments, the method  1000  provides a motion collection-based technique for mitigation of oversampled data. Whereas, in some embodiments, the method  1000  provides a point distance rejection-based technique for mitigation of oversampled data. Yet, in some embodiments, the method  1000  provides a point density rejection-based technique for mitigation of oversampled data. 
       FIG.  2    is a flow diagram depicting an example of a motion collection-based oversampling mitigation method  2000  in accordance with some embodiments of the method  1000 . For example, the method  2000  can be used to limit the collection of survey data until motor encoder values from either  10  or pitch/yaw have changed enough to qualify as motion of the medical device, such as a catheter. All or a subset of the steps of the method  2000  can be implemented by the computing device, e.g., such as the control system  112  of the medical system  100  described later, or various other components or devices of a robotic or teleoperated system. In various implementations of the method  2000 , for example, the sensor can include the shape sensor  233  and/or the position measuring device  239  of the medical instrument system  204 , and the method  2000  can be implemented during surveying of an anatomic structure or structures of a patient, such as in a registration protocol during an implementation of the sensor system  208 . 
     At process  2010 , the method  2000  receives survey data points detected by the sensor of the medical device (e.g., shape sensor  233 ) for determining when the medical device is moved in one or more particular translational and/or rotational motions, e.g., roll motion (delta $) or pitch or yaw motions. During surveying by the sensor (process  2010 ), the method  2000  includes a process  2020  to determine a change of the translational and/or rotational motion (e.g., delta  10  or pitch/yaw values). At process  2030 , the method compares the change to a threshold (e.g., threshold value or range of values) associated with the translational and/or rotational motion. At process  2040 , the method  2000  records survey data points in the point cloud when the determined change in motion meets the threshold, and not record (e.g., discard) the survey data points in the point cloud when the determined change in motion does not meet the threshold. In this manner, for example, the method  2000  can limit the collection of survey data that will be included in the point cloud based on the sensor (e.g., encoder) values of a particular magnitude, such as a substantial change in IO or pitch/yaw, to qualify as motion of the medical device within the anatomic region during registration—not just simple movement of the medical device. 
     In an example implementation of the method  2000 , the shape sensor  233  and/or the position measuring device  239  of the medical instrument system  204  is driven in one or multiple anatomic passageways of the patient. At the process  2010 , the control system  112  of the medical system  100  receives all of the data generated by the shape sensor  233  and/or the position measuring device  239 . At the process  2020 , the control system  112  determines whether there is a change in movement and/or position of the shape sensor  233  and/or the position measuring device  239 ; and if there is a determined change, the control system  112  determines a value of the change, i.e., a delta of the movement and/or a delta of the position. If no change is determined, the control system  112  assigns a delta of zero to the movement and/or position parameter (e.g., the first parameter). At the process  2030 , the control system  112  compares the determined value of the change to a threshold value (or range of threshold values) for determining whether to accept or reject the received survey data sampled from the medical instrument system  204 . In one non-limiting example, the threshold value is 0.5 mm in a position change from the previously collected point. The threshold value (or threshold range) can be predetermined and stored in the memory of the control system  112 . At the process  2040 , the control system  112  records the survey data points in the point cloud when it is determined at the process  2030  that the determined value of the change meets the threshold value. For example, when the delta is zero or less than the threshold (or outside of any threshold range), the survey data will be rejected at the process  2040 . For example, when the delta is at or greater than the threshold (or within a threshold range), the survey data will be accepted at the process  2040 . In this manner, the method  2000  mitigates potential oversampling by the system  100  by using only the accepted data to register the medical instrument system  204  in anatomic space (e.g., which corresponds with an image space from a pre-operation image). 
       FIG.  3    is a flow diagram depicting an example of a point distance rejection-based oversampling mitigation method  3000  in accordance with some embodiments of the method  1000 . All or a subset of the steps of the method  3000  can be implemented by the computing device, such as the control system  112  of the medical system  100 , or various other components or devices of a robotic or teleoperated system. In various implementations of the method  3000 , for example, the sensor can include the shape sensor  233  and/or of the position measuring device  239  of the medical instrument system  204 , and the method  3000  can be implemented during surveying of an anatomic structure or structures of a patient, e.g., such as in a registration protocol during an implementation of the sensor system  208 . 
     At process  3010 , the method  3000  receives survey data points detected by the sensor of the medical device (e.g., shape sensor  233  at tip and/or body), which are recorded to a sampled survey point cloud. At process  3020 , the method  3000  determines, e.g., in real-time during surveying by the sensor (e.g., at process  3010 ), a distance from a data point to its nearest neighbor within the sampled survey point cloud. At process  3030 , the method  3000  compares the determined distance to a threshold distance, e.g., threshold distance value or range of distance values. At process  3040 , the method  3000  rejects a data point from the recorded sampled survey point cloud when the determined distance of that data point is within the threshold distance of the nearest neighbor. In this manner, for example, the method  3000  adds the surveyed data points to the point cloud and rejects those data points whose distance are determined to be too close to nearest neighbors, e.g., in a real-time evaluation during a registration protocol of the medical device. 
     In an example implementation of the method  3000 , the shape sensor  233  and/or the position measuring device  239  of the medical instrument system  204  is driven in one or multiple anatomic passageways of the patient. At the process  3010 , the control system  112  of the medical system  100  receives all of the data generated by the shape sensor  233  and/or the position measuring device  239  and initially records all of the data to the point cloud. At the process  3020 , the control system  112  examines at least a set of the recorded data to the point cloud by determining a distance of a data point or data points within the set to other nearest neighbor data points within the set. At the process  3030 , the determined distance between each data point and its nearest neighbors is compared to a threshold (e.g., a threshold value or a threshold range), e.g., which provides the control system  112  with a ‘degree of closeness’ of the data point to its nearest neighbors. In implementations of the processes  3020  and  3030 , for example, the control system  112  can calculate a set of K nearest neighbor distances and evaluate the point using any number of nearest neighbors. In one case, the number of nearest neighbors, K, may be specified by the user or software. Alternatively, the number of nearest neighbors may be determined as the set of all points that lie within a specified distance from the point in question. At the process  3040 , the data points determined to be ‘too close’ to their nearest neighbors (i.e., its distance is within the threshold distance of its nearest neighbor(s)), are rejected from the point cloud. 
       FIG.  4    is a flow diagram depicting an example of a point density rejection-based oversampling mitigation method,  4000  in accordance with some embodiments of the method  1000 . All or a subset of the steps of the method  4000  can be implemented by the computing device, such as the control system  112  of the medical system  100 , or various other components or devices of a robotic or teleoperated system. In various implementations of the method  4000 , for example, the sensor can include the shape sensor  233  and/or of the position measuring device  239  of the medical instrument system  204 , and the method  4000  can be implemented during surveying of an anatomic structure or structures of a patient, e.g., such as in a registration protocol during an implementation of the sensor system  208 . 
     At process  4010 , the method  4000  receives survey data points detected by the sensor of the medical device (e.g., shape sensor  233  at tip and/or body), which are recorded to a sampled survey point cloud. At process  4020 , the method  4000  determines, e.g., in real-time during surveying by the sensor (e.g., at process  4010 ), a density of the data points, e.g., within a subset of the sampled survey point cloud corresponding to a sub-region of the anatomic structure (e.g., predefined subset). At process  4030 , the method  4000  compares the determined density to a threshold density, e.g., threshold density value or range of density values. At process  4040 , the method  4000  rejects a data point from the recorded sampled survey point cloud when the determined density of data points (that encompasses that data point) is within the threshold density of the sub-region. In this manner, for example, the method  4000  adds the surveyed data points to the point cloud and rejects them in real-time upon evaluation with respect to a point density threshold, e.g., which can be a point density threshold within a region or regions (of various sizes, e.g., predefined) of the anatomic structure. 
     In an example implementation of the method  4000 , the shape sensor  233  and/or the position measuring device  239  of the medical instrument system  204  is driven in one or multiple anatomic passageways of the patient. At the process  4010 , the control system  112  of the medical system  100  receives all of the data generated by the shape sensor  233  and/or the position measuring device  239  and initially records all of the data to the point cloud. At the process  4020 , the control system  112  begins examining the density of data points within a set of the recorded data to the point cloud. For example, at process  4020 , the control system  112  determines a density of data points within the set that includes an analysis of the data points within the set with respect to their nearest neighbor data points. At the process  4030 , the determined density of data points within the set is compared to a threshold (e.g., a threshold value or a threshold range), e.g., which provides the control system  112  with a ‘degree of denseness’ of the data points with respect to their nearest neighbors within the set. In implementations of the processes  4020  and  4030 , for example, the control system  112  can calculate a set of K nearest neighbor distances and evaluate each point using any number of nearest neighbors. When the set is determined to be ‘too dense’ within data points, the control system  112  can reject data point(s) to mitigate the oversampling. At the process  4040 , the data points determined to be in a ‘dense set’ with respect to their nearest neighbors are rejected from the point cloud. 
       FIG.  5    is a flow diagram depicting an example of a survey density normalization-based oversampling mitigation method  5000  in accordance with some embodiments of the method  1000 . Like the methods described above, all or a subset of the steps of the method  5000  can be implemented by a computing device, such as the control system  112  of the medical system  100 , or various other components or devices of a robotic or teleoperated system. In various implementations of the method  5000 , the sensor can include the shape sensor  233  and/or of the position measuring device  239  of the medical instrument system  204 , and the method  5000  can be implemented during surveying of an anatomic structure or structures of a patient, e.g., such as in a registration protocol during an implementation of the sensor system  208 . 
     In some examples of the method  5000 , survey data points would be collected by the sensor, but certain data points might be removed if over-sampled in a given region. For example, a straight-forward approach would be to keep all points but to decrease the per-point weighting within densely surveyed regions, which can be implemented as an augmentation to the ICP algorithm because weighting is already a variable employed by standard ICP algorithms. Within an example ICP algorithm, a registration is computed at each step using the cumulative set of nearest-neighbor matches between the surveyed point cloud and the comparative data set of the anatomic structure, e.g., a pre-operative image data set of an airway tree. In implementations of the method  5000 , for example, by reducing the weighting applied to point matches within a given region, the method can effectively down-weight or correct for over-sampling in that region. The method  5000  includes a set of operations or processes  5010 - 5040  described below. 
     At process  5010 , the method  5000  receives survey data points detected by the sensor of the medical device (e.g., shape sensor  233 ), which can be recorded to a sampled survey point cloud based on the outcomes of the processes  5020  and  5030 . At process  5020 , the method  5000  determines, e.g., in real-time during surveying by the sensor (e.g., at process  5010 ), a density of the data points, e.g., within a subset of the sampled survey point cloud corresponding to a sub-region of the anatomic structure (e.g., predefined subset). In some implementations of the process  5010 , for example, the determined density is based on distance parameters from medical device&#39;s location within the anatomic region. At process  5030 , the method  5040  compares the determined density to a threshold density for the sub-region, e.g., threshold density value or range of density values. 
     The method  5000  includes a process  5040  to (i) record the collected survey data points to the survey point cloud and (ii) decrease the weighting value associated with a data point within the sub-region when the determined density exceeds the threshold density (e.g., referred to as oversampled sub-region). In some implementations of the process  5040 , for example, the weighting value is normalized for weighting values associated with data points in the over-sampled sub-region, where the normalization process includes dividing weighting by total number of matches to nearest survey points. As an illustrative example, the process  5040  can be implemented where the weighting would be normalized such that points in the anatomic structures, like the pulmonary airway tree, that are nearest to multiple survey points would have their weighting divided by the total number of matches. In some examples, matches could be down-weighted or up-weighted depending on the local density of points. In such cases, for example, the density can be computed based on the number of survey points in a given volume. 
     Yet, in some implementations of the process  5040 , the weighting value is normalized by smoothing data points along a length line traversing at least a portion of the over-sampled sub-region. As an illustrative example, the process  5040  can be implemented where the density is normalized by computing the number of matches that occur along a given length of the anatomic structure (e.g., an airway in a pulmonary airway tree). In such a case, for example, larger areas of over-sampling can be smoothed out by normalizing the local weighting density of all survey points along each airway. The result would be that the registration is balanced over the total length of driven airways. 
     Embodiments of Robotic or Teleoperated Medical Systems for Implementing the Disclosed Methods 
       FIG.  6    is a schematic representation of a robotic or teleoperated medical system  100  (“medical system  100 ”) configured in accordance with various embodiments of the present technology. As shown, the medical system  100  includes a manipulator assembly  102 , a medical instrument system  104 , a master assembly  106 , and a control system  112 . The manipulator assembly  102  supports the medical instrument system  104  and drives the medical instrument system  104  at the direction of the master assembly  106  and/or the control system  112  to perform various medical procedures on a patient  103  positioned on a table  107  in a surgical environment  101 . In this regard, the master assembly  106  generally includes one or more control devices that can be operated by an operator  105  (e.g., which can be a physician) to control the manipulator assembly  102 . Additionally, or alternatively, the control system  112  includes a computer processor  114  and at least one memory  116  for effecting control between the medical instrument system  104 , the master assembly  106 , and/or other components of the medical system  100 . The control system  112  can also include programmed instructions (e.g., a non-transitory computer-readable medium storing the instructions) to implement any one or more of the methods described herein, including instructions for providing information to a display system  110  and/or processing data for registration of the medical instrument  104  for various medical procedures on the patient by the medical system  100  (as described in greater detail below). The manipulator assembly  102  can be a teleoperated, a non-teleoperated, or a hybrid teleoperated and non-teleoperated assembly. Thus, all or a portion of the master assembly  106  and/or all or a portion of the control system  112  can be positioned inside or outside of the surgical environment  101 . 
     In some embodiments, to aid the operator  105  in controlling the manipulator assembly  102  and the medical instrument system  104 , the medical system  100  further includes a sensor system  108 , an endoscopic imaging system  109 , an imaging system  118 , a virtual visualization system  115 , and/or the display system  110 . In some embodiments, the sensor system  108  includes a position/location sensor system (e.g., an electromagnetic (EM) sensor system) and/or a shape sensor system for determining position, orientation, speed, velocity, pose, and/or shape of the medical instrument system  104  (e.g., while the medical instrument system  104  is within the patient  103 ). In these and other embodiments, the endoscopic imaging system  109  includes one or more image capture devices (not shown) (e.g., such as an imaging scope assembly and/or an imaging instrument) that records endoscopic image data, including concurrent or real-time images (e.g., video, still images, etc.) of patient anatomy. Images captured by the endoscopic imaging system  109  may be, for example, two or three-dimensional images of patient anatomy captured by an imaging instrument positioned within the patient  103 , and are referred to hereinafter as “real navigational images.” 
     In some embodiments, the medical instrument system  104  may include components of the sensor system  108  and/or of the endoscopic imaging system  109 . For example, components of the sensor system  108  and/or components of the endoscopic imaging system  109  can be integrally or removably coupled to the medical instrument system  104 . Additionally, or alternatively, the endoscopic imaging system  109  can include a separate endoscope (not shown) attached to a separate manipulator assembly (not shown) that can be used in conjunction with the medical instrument system  104  to image patient anatomy. The sensor system  108  and/or the endoscopic imaging system  109  may be implemented as hardware, firmware, software, or a combination thereof that interact with or are otherwise executed by one or more computer processors, such as the computer processor(s)  114  of the control system  112 . 
     The imaging system  118  of the medical system  100  may be arranged in the surgical environment  101  near the patient  103  to obtain real-time and/or near real-time images of the patient  103  before, during, and/or after a medical procedure. In some embodiments, the imaging system  118  includes a mobile C-arm cone-beam computerized tomography (CT) imaging system for generating three-dimensional images. For example, the imaging system  118  can include a DynaCT imaging system from Siemens Corporation or another suitable imaging system. In these and other embodiments, the imaging system  118  can include other imaging technologies, including magnetic resonance imaging (MRI), fluoroscopy, thermography, ultrasound, optical coherence tomography (OCT), thermal imaging, impedance imaging, laser imaging, nanotube X-ray imaging, and/or the like. 
     In these and other embodiments, the control system  112  further includes the virtual visualization system  115  to provide navigation assistance to the operator  105  when controlling the medical instrument system  104  during an image-guided medical procedure. For example, virtual navigation using the virtual visualization system  115  can be based upon reference to an acquired pre-operative or intra-operative dataset (e.g., based upon reference to data generated by the sensor system  108 , the endoscopic imaging system  109 , and/or the imaging system  118 ) of anatomic passageways of the patient  103 . In some implementations, for example, the virtual visualization system  115  processes image data of the patient anatomy captured using the imaging system  118  (e.g., to generate an anatomic model of an anatomic region of the patient  103 ). The virtual visualization system  115  can register the image data and/or the anatomic model to data generated by the sensor system  108  and/or to data generated by the endoscopic imaging system  109  to (i) determine position, pose, orientation, shape, and/or movement of the medical instrument system  104  within the anatomic model (e.g., to generate a composite virtual navigational image), and/or (ii) determine a virtual image (not shown) of patient anatomy from a viewpoint of the medical instrument system  104  within the patient  103 . For example, the virtual visualization system  115  can register the anatomic model to positional sensor data generated by the positional sensor system  108  and/or to endoscopic image data generated by the endoscopic imaging system  109  to (i) map the tracked position, orientation, pose, shape, and/or movement of the medical instrument system  104  within the anatomic region to a correct position within the anatomic model, and/or (ii) determine a virtual navigational image of virtual patient anatomy of the anatomic region from a viewpoint of the medical instrument system  104  at a location within the anatomic model corresponding to a location of the medical instrument system  104  within the patient  103 . 
     The display system  110  can display various images or representations of patient anatomy and/or of the medical instrument system  104  that are generated by the sensor system  108 , by the endoscopic imaging system  109 , by the imaging system  118 , and/or by the virtual visualization system  115 . In some embodiments, the display system  110  and/or the master assembly  106  may be oriented so the operator  105  can control the manipulator assembly  102 , the medical instrument system  104 , the master assembly  106 , and/or the control system  112  with the perception of telepresence. 
     As discussed above, the manipulator assembly  102  drives the medical instrument system  104  at the direction of the master assembly  106  and/or the control system  112 . In this regard, the manipulator assembly  102  can include select degrees of freedom of motion that may be motorized and/or teleoperated and select degrees of freedom of motion that may be non-motorized and/or non-teleoperated. For example, the manipulator assembly  102  can include a plurality of actuators or motors (not shown) that drive inputs on the medical instrument system  104  in response to commands from the control system  112 . The actuators can include drive systems (not shown) that, when coupled to the medical instrument system  104 , can advance the medical instrument system  104  into a naturally or surgically created anatomic orifice. Other drive systems may move a distal portion (not shown) of the medical instrument system  104  in multiple degrees of freedom, which may include three degrees of linear motion (e.g., linear motion along the X, Y, Z Cartesian axes) and three degrees of rotational motion (e.g., rotation about the X, Y, Z Cartesian axes). Additionally, the actuators can be used to actuate an articulable end effector of the medical instrument system  104  (e.g., for grasping tissue in the jaws of a biopsy device and/or the like). 
       FIG.  7    is a schematic representation of a manipulator assembly  202 , a medical instrument system  204 , and an imaging system  218  in a surgical environment  201  and configured in accordance with various embodiments of the present technology. In some embodiments, the manipulator assembly  202 , the medical instrument system  204 , and/or the imaging system  218  are the manipulator assembly  102 , the medical instrument system  104 , and/or the imaging system  118 , respectively, of  FIG.  6   . As shown, the surgical environment  201  illustrated in  FIG.  7    has a surgical frame of reference (X S , Y S , Z S ) in which a patient  203  is positioned on a table  207 , and the medical instrument system  204  illustrated in  FIG.  7    has a medical instrument frame of reference (X M , Y M , Z M ) within the surgical environment  201 . During the medical procedure, the patient  203  may be stationary within the surgical environment  201  in the sense that gross patient movement can be limited by sedation, restraint, and/or other means. In these and other embodiments, cyclic anatomic motion of the patient  203 , including respiration and cardiac motion, may continue unless the patient  203  is asked to hold his or her breath to temporarily suspend respiratory motion. 
     The manipulator assembly  202  includes an instrument carriage  226  mounted to an insertion stage  228 . In some embodiments, the insertion stage  228  is fixed within the surgical environment  201 . Alternatively, the insertion stage  228  can be movable within the surgical environment  201  but have a known location (e.g., via a tracking sensor or other tracking device) within the surgical environment  201 . In these alternatives, the medical instrument frame of reference (X M , Y M , Z M ) is fixed or otherwise known relative to the surgical frame of reference (X S , Y S , Z S ). In the illustrated embodiment, the insertion stage  228  is linear, while in other embodiments, the insertion stage  228  is curved or has a combination of curved and linear sections. 
     The medical instrument system  204  of  FIG.  7    includes an elongate device  231 , a medical instrument  232 , an instrument body  235 , a sensor system  208 , and an endoscopic imaging system  209 . In some embodiments, the elongate device  231  is a flexible catheter that defines a channel or lumen  244 . The channel  244  can be sized and shaped to receive the medical instrument  232  (e.g., via a proximal end  236  and/or an instrument port (not shown) of the elongate device  231 ) and facilitate delivery of the medical instrument  232  to a distal portion  238  of the elongate device  231 . As shown, the elongate device  231  is coupled to the instrument body  235 , which in turn is coupled and fixed relative to the instrument carriage  226  of the manipulator assembly  202 . 
     In operation, for example, the manipulator assembly  202  can control insertion motion (e.g., proximal and/or distal motion along an axis A) of the elongate device  231  into the patient  203  via a natural or surgically created anatomic orifice of the patient  203  to facilitate navigation of the elongate device  231  through anatomic passageways of the patient  203  and/or to facilitate delivery of the distal portion  238  of the elongate device  231  to a target location within the patient  203 . For example, the instrument carriage  226  and/or the insertion stage  228  may include actuators (not shown), such as servomotors, that facilitate control over motion of the instrument carriage  226  along the insertion stage  228 . Additionally, or alternatively, the manipulator assembly  202  in some embodiments can control motion of the distal portion  238  of the elongate device  231  in multiple directions, including yaw, pitch, and roll rotational directions (e.g., to navigate patient anatomy). To this end, the elongate device  231  may house or include cables, linkages, and/or other steering controls (not shown) that the manipulator assembly  202  can use to controllably bend the distal portion  238  of the elongate device  231 . For example, the elongate device  231  can house at least four cables that can be used by the manipulator assembly  202  to provide (i) independent “up-down” steering to control a pitch of the distal portion  238  of the elongate device  231  and (ii) independent “left-right” steering of the elongate device  231  to control a yaw of the distal portion  238  of the elongate device  231 . 
     The medical instrument  232  of the medical instrument system  204  can be used for medical procedures, such as for survey of anatomical passageways, surgery, biopsy, ablation, illumination, irrigation, and/or suction. Thus, the medical instrument  232  can include image capture probes, biopsy instruments, laser ablation fibers, and/or other surgical, diagnostic, and/or therapeutic tools. For example, the medical instrument  232  can include an endoscope having one or more image capture devices  247  positioned at a distal portion  237  of and/or at other locations along the medical instrument  232 . In these embodiments, the image capture device  247  can capture one or more real images or video (e.g., a sequence of one or more real navigation image frames) of anatomic passageways and/or other patient anatomy while the medical instrument  232  is within the anatomic region of the patient  203 . 
     As discussed above, the medical instrument  232  can be deployed into and/or be delivered to a target location within the patient  203  via the channel  244  defined by the elongate device  231 . In embodiments in which the medical instrument  232  includes an endoscope or other medical device having the image capture device  247  at the distal portion  237  of the medical instrument  232 , the image capture device  247  can be advanced to the distal portion  238  of the elongate device  231  before, during, and/or after the manipulator assembly  202  navigates the distal portion  238  of the elongate device  231  to a target location within the patient  203 . In these embodiments, the medical instrument  232  can be used as a survey instrument to capture real images and/or video of anatomic passageways and/or other patient anatomy, and/or to aid the operator (e.g., a physician) to navigate the distal portion  238  of the elongate device  231  through anatomic passageways to the target location. 
     As another example, after the manipulator assembly  202  positions the distal portion  238  of the elongate device  231  proximate a target location within the patient  203 , the medical instrument  232  can be advanced beyond the distal portion  238  of the elongate device  231  to perform a medical procedure at the target location. Continuing with the above example, after all or a portion of the medical procedure at the target location is complete, the medical instrument  232  can be retracted back into the elongate device  231  and, additionally or alternatively, be removed from the proximal end  236  of the elongate device  231  or from another instrument port (not shown) along the elongate device  231 . 
     In the example embodiment shown in  FIG.  7   , the sensor system  208  of the medical instrument system  204  includes a shape sensor  233  and a position measuring device  239 . In some embodiments, the sensor system  208  includes all or a portion of the sensor system  108  of  FIG.  6   . In these and other embodiments, the shape sensor  233  of the sensor system  208  includes an optical fiber extending within and aligned with the elongate device  231 . In one embodiment, the optical fiber of the shape sensor  233  has a diameter of approximately 200 μm. In other embodiments, the diameter of the optical fiber may be larger or smaller. 
     The optical fiber of the shape sensor  233  forms a fiber optic bend sensor that is used to determine a shape of the elongate device  231 . In some embodiments, optical fibers having Fiber Bragg Gratings (FBGs) can be used to provide strain measurements in structures in one or more dimensions. Various systems and methods for monitoring the shape and relative position of an optical fiber in three dimensions are described in further detail in U.S. Patent Application Publication No. 2006-0013523 (filed Jul. 13, 2005) (disclosing fiber optic position and shape sensing device and method relating thereto); U.S. Pat. No. 7,781,724 (filed on Sep. 26, 2006) (disclosing fiber-optic position and shape sensing device and method relating thereto); U.S. Pat. No. 7,772,541 (filed on Mar. 12, 2008), (disclosing fiber-optic position and/or shape sensing based on Rayleigh scatter); and U.S. Pat. No. 6,389,187 (filed on Jun. 17, 1998) (disclosing optical fiber bend sensor), which are all incorporated by reference herein in their entireties. In these and other embodiments, sensors of the present technology may employ other suitable strain sensing techniques, such as Rayleigh scattering, Raman scattering, Brillouin scattering, and Fluorescence scattering. In these and still other embodiments, the shape of the elongate device  231  may be determined using other techniques. For example, a history of the pose of the distal portion  238  of the elongate device  231  can be used to reconstruct the shape of elongate device  230  over an interval of time. 
     In some embodiments, the shape sensor  233  is fixed at a proximal point  234  on the instrument body  235  of the medical instrument system  204 . In operation, for example, the shape sensor  233  measures a shape in the medical instrument reference frame (X M , Y M , Z M ) from the proximal point  234  to another point along the optical fiber, such as the distal portion  238  of the elongate device  231 . The proximal point  234  of the shape sensor  233  may be movable along with instrument body  235  but the location of proximal point  234  may be known (e.g., via a tracking sensor or other tracking device). 
     The position measuring device  239  of the sensor system  208  provides information about the position of the instrument body  235  as it moves along the insertion axis A on the insertion stage  228  of the manipulator assembly  202 . In some embodiments, the position measuring device  239  includes resolvers, encoders, potentiometers, and/or other sensors that determine the rotation and/or orientation of actuators (not shown) controlling the motion of the instrument carriage  226  of the manipulator assembly  202  and, consequently, the motion of the instrument body  235  of the medical instrument system  204 . 
       FIG.  8    is a schematic representation of a portion of the medical instrument system  204  of  FIG.  7    extended within an anatomic region  350  (e.g., human lungs) of the patient  203  in accordance with various embodiments of the present technology. In particular,  FIG.  8    illustrates the elongate device  231  of the medical instrument system  204  extending within branched anatomic passageways  352  of the anatomic region  350 . The anatomic passageways  352  include a trachea  354  and bronchial tubes  356 . 
     As shown in  FIG.  8   , the elongate device  231  has a position, orientation, pose, and shape within the anatomic region  350 , all or a portion of which (in addition to or in lieu of movement, such as speed or velocity) can be captured by the shape sensor  233  and/or the position measuring device  239  of the sensor system  208  to survey the anatomic passageways  352  of the anatomic region  350 . In particular, the shape sensor  233  and/or the position measuring device  239  of the sensor system  208  can survey the anatomic passageways  352  by gathering positional information of the medical instrument system  204  within the anatomic region  350  in the medical instrument frame of reference (X M , Y M , Z M ). The positional information may be recorded as a set of two-dimensional or three-dimensional coordinate points. In the example of the anatomic region  350  being human lungs, the coordinate points may represent the locations of the distal portion  238  of the elongate device  231  and/or other portions of the elongate device  231  while the elongate device  231  is advanced through the trachea  354  and the bronchial tubes  356 . In these and other embodiments, the collection of coordinate points may represent the shape(s) of the elongate device  231  while the elongate device  231  is advanced through the anatomic region  350 . In these and other embodiments, the coordinate points may represent positional data of other portions (e.g., the medical instrument  232 ) of the medical instrument system  104 . 
     The coordinate points may together form positional point cloud data. For example,  FIG.  9    illustrates a plurality of coordinate points  462  forming positional point cloud data  460  representing a shape of the elongate device  231  while the elongate device  231  is within the anatomic region  350  (previously shown in  FIG.  8   ) in accordance with various embodiments of the present technology. In particular, the positional point cloud data  460  is generated from the union of all or a subset of the recorded coordinate points  462  of the shape sensor  233  (previously shown in  FIGS.  7  and  8   ) and/or of the position measuring device  239  (previously shown in  FIG.  7   ) during a data acquisition period by the sensor system  208 . The positional point cloud data  460  can be generated by implementation of the disclosed example embodiments of the method  1000 . 
     In some embodiments, a point cloud (e.g., the point cloud  460 ) can include the union of all or a subset of coordinate points recorded by the sensor system  208  during an image capture period that spans multiple shapes, positions, orientations, and/or poses of the elongate device  231  within the anatomic region  350 . In these embodiments, the point cloud can include coordinate points captured by the sensor system  208  that represent multiple shapes of the elongate device  231  while the elongate device  231  is advanced or moved through patient anatomy during the image capture period. Additionally, or alternatively, because the configuration, including shape and location, of the elongate device  231  within the patient  203  may change during the image capture period due to anatomical motion, the point cloud in some embodiments can comprise a plurality of coordinate points  462  captured by the sensor system  208  that represent the shapes of the elongate device  231  as the elongate device  231  passively moves within the patient  203 . A point cloud of coordinate points captured by the sensor system  208  can be registered to different models or datasets of patient anatomy. For example, the positional point cloud data  460  can be used in registration with different models of the branched anatomic passageways  352 . 
     Referring again to  FIG.  7   , the endoscopic imaging system  209  of the medical instrument system  204  includes one or more image capture devices configured to capture one or more images and/or video (e.g., a sequence of image frames) of anatomic passageways (e.g., the anatomic passageways  352  of  FIG.  8   ) and/or other patient anatomy while the elongate device  231  and/or the medical instrument  232  is within the patient  203 . For example, the endoscopic imaging system  209  can include (i) the image capture device  247  positioned at the distal portion  237  of the medical device  232  and/or (ii) one or more other image capture devices (not shown) positioned at other locations along the medical device  232 . In these and other embodiments, the endoscopic imaging system  209  can include one or more image capture devices (not shown) positioned at the distal portion  238  and/or other locations along the elongate device  231 . In some embodiments, the endoscopic imaging system  209  can include all or a portion of the endoscopic imaging system  109  of  FIG.  6   . 
     As shown in  FIG.  8   , the image capture device  247  of the medical instrument  234  is positioned at the distal portion  238  of the elongate device  231 . In this embodiment, the image capture device  247  surveys the anatomic passageways  352  by capturing real images of the anatomic passageways  352  while the elongate device  231  is advanced through the trachea  354  and the bronchial tubes  356  of the anatomic region  350 . 
       FIG.  10    is an example of an endoscopic video image frame  570  (e.g., a real image, such as a still image, an image frame of a video, etc.) of patient anatomy of the anatomic region  350  such as the anatomic passageways  352  of  FIG.  8    captured using the image capture device  247  of the medical instrument system  204 . As shown, the real image  570  illustrates a branching point  571  of two bronchial tubes  356  (within the anatomic region  350  illustrated in  FIG.  8   ) from a viewpoint of the medical instrument  232 . In this example, the viewpoint is from the distal tip of the medical instrument  232 , such that the medical instrument  232  is not visible within the real image  570 . In other embodiments, the image capture device  247  can be positioned at another location along the medical instrument  232  and/or along the elongate device  231  such that the real image  570  is taken from another viewpoint of the medical instrument  232  and/or from another viewpoint of the elongate device  231 . A portion of the medical device  232  and/or of the elongate device  231  may be visible within the real image  570  depending on the positions of the medical instrument  232  and the elongate device  231  relative to one another. 
     Referring again to  FIG.  7   , the real images captured by the endoscopic imaging system  209  can facilitate navigation of the distal portion  238  of the elongate device  231  through anatomic passageways (e.g., the anatomic passageways  352  of  FIG.  8   ) of the patient  203  and/or delivery of the distal portion  238  of the elongate device  231  to a target location within the patient  203 . In these and other embodiments, the real images captured by the endoscopic imaging system  209  can facilitate (i) navigation of the distal portion of the medical instrument  232  beyond the distal portion  238  of the elongate device  231 , (ii) delivery of the distal portion of the medical instrument  232  to a target location within the patient  203 , and/or (iii) visualization of patient anatomy during a medical procedure. In some embodiments, each real image captured by the endoscopic imaging system  209  can be associated with a time stamp and/or a position within an anatomic region of the patient  203 . 
     As illustrated in  FIG.  7   , the imaging system  218  can be arranged near the patient  203  to obtain three-dimensional images of the patient  203 . In some embodiments, the imaging system  218  includes one or more imaging technologies, including CT, MRI, fluoroscopy, thermography, ultrasound, OCT, thermal imaging, impedance imaging, laser imaging, nanotube X-ray imaging, and/or the like. The imaging system  218  is configured to generate image data of the patient  203  before, during, and/or after the elongate device  231  is extended within the patient  203 . Thus, the imaging system  218  can be configured to capture preoperative, intraoperative, and/or postoperative three-dimensional images of the patient  203 . In these and other embodiments, the imaging system  218  may provide real-time or near real-time images of the patient  203 . 
       FIG.  11    illustrates such intra-operative image data  680  of a portion  655  of the anatomic region  350  of  FIG.  8    captured during an image capture period by the imaging system  218  while the elongate device  231  of the medical instrument system  204  is extended within the anatomic region  350 . As shown, the image data  680  includes graphical elements  681  representing the elongate device  231  and graphical elements  682  representing the anatomical passageways  352  of the anatomic region  350 . 
     All or a portion of the graphical elements  681  and  682  of the image data  680  can be segmented and/or filtered to generate (i) a three-dimensional model of the anatomical passageways  352  of the portion  655  of the anatomic region  350 , and/or (ii) an image point cloud of the elongate device  231  within the anatomic region  350 . During the segmentation process, pixels or voxels generated from the image data  680  may be partitioned into segments or elements or be tagged to indicate that they share certain characteristics or computed properties such as color, density, intensity, and texture. The segments or elements may then be converted to a model and/or a point cloud. Additionally, or alternatively, the segments or elements can be used to locate (e.g., calculate) and/or define a center line running along the anatomical passageways  352 . The generated anatomic models and/or point clouds may be two or three-dimensional and may be generated in an image reference frame (X 1 , Y 1 , Z 1 ). 
     As discussed above with respect to  FIG.  6   , the display system  110  of the medical system  100  can display various images or representations of patient anatomy and/or of the medical instrument system  104  based on data captured and/or generated by the positional sensor system  108 , by the endoscopic imaging system  109 , by the imaging system  118 , and/or by the virtual visualization system  115 . In various implementations, the images and/or representations can be utilized by the system to aid the operator  105  in conducting an image-guided medical procedure. 
       FIG.  12    is a schematic representation of an example display  710  produced by the display system  110  in accordance with various embodiments of the present technology. As shown, the display  710  includes a real navigational image  770 , a composite virtual navigational image  791  (also referred to as “composite virtual image  791 ”), and a virtual navigational image  792 . The real navigational image  770  can be substantially the same as the real navigational image  570  of  FIG.  10   . Thus, for example, the real navigational image  770  can be captured by the endoscopic imaging system  109  ( FIG.  7   ) and provided to the display system  110  to be presented on the display  710  in real-time or near real-time. In the illustrated embodiment, the real navigational image  770  illustrates real patient anatomy, e.g., such as a real image of a branching point or carina  771  at which an anatomic passageway branches into the two bronchial tubes  356  and/or anatomic passageways  352 ) from a viewpoint oriented distally away from the distal portion  237  of the medical instrument  232 . 
     The composite virtual image  791  of  FIG.  12    is displayed in the image reference frame (X 1 , Y 1 , Z 1 ) and includes an anatomic model  796  generated from image data (e.g., of the anatomic region  350  of  FIG.  8   ) captured by the imaging system  118 . The anatomic model  796  is registered (i.e., dynamically referenced) with a point cloud of coordinate points (e.g., the point cloud  460  of  FIG.  9   ) generated by the positional sensor system  108  to display a representation  704  within the anatomic model  796  of the tracked position, shape, pose, orientation, and/or movement of embodiments of the medical instrument system  104  (e.g., such as of the elongate device  231  of  FIG.  7   ) within the patient  103 . In some embodiments, the composite virtual image  791  is generated by the virtual visualization system  115  ( FIG.  6   ) of the control system  112  ( FIG.  6   ). Generating the composite virtual image  791  involves registering the image reference frame (X 1 , Y 1 , Z 1 ) with the surgical reference frame (X S , Y S , Z S ) and/or to the medical instrument reference frame (X M , Y M , Z M ). This registration may rotate, translate, or otherwise manipulate by rigid and/or non-rigid transforms coordinate points of the point cloud (e.g., the coordinate points  462  of the point cloud  460  of  FIG.  9   ) captured by the positional sensor system  108  to align the coordinate points with the anatomic model  796 . The registration between the image and surgical/instrument frames of reference may be achieved, for example, by using a point-based iterative closest point (ICP) technique as described in U.S. Provisional Pat. App. Nos. 62/205,440 and No. 62/205,433, which are both incorporated by reference herein in their entireties. In other embodiments, the registration can be achieved using another point cloud registration technique. 
     Based at least in part on the registration, the virtual visualization system  115  can additionally or alternatively generate virtual navigational images (e.g., the virtual navigational image  792 ) that include a virtual depiction of patient anatomy from a viewpoint of a virtual camera on the representation  704  of the medical instrument system  104  ( FIG.  9   ) within the anatomic model  796 . In the embodiment illustrated in  FIG.  12    of the representation  704  of the medical instrument system  204  shown in  FIG.  7   , the virtual camera is positioned at the distal portion  737  of representation  704  (e.g., of the medical instrument  232 ) such that (i) the viewpoint of the virtual navigational image  792  (shown in  FIG.  12   ) is directed distally away from the distal portion  737  of the representation  704  and (ii) the representation  704  is not visible within the virtual navigational image  792 . In other embodiments, the virtual visualization system  115  can position the virtual camera (i) at another location along the representation  704  and/or (ii) in a different orientation such that the virtual navigational image  792  has a corresponding virtual viewpoint. In some embodiments, depending on the position and orientation of the virtual camera and the positions of the elongate device  231  and the medical instrument  232  relative to one another when within the patient  103 , the virtual visualization system  115  can render a virtual representation (not shown) of at least a portion of the elongate device  231  and/or of the medical instrument  232  into the virtual navigational image  792 . 
     In some embodiments, the virtual navigational image  792  can optionally include a navigation stripe  799 . In some implementations, for example, the navigation stripe  799  is used to aid the operator  105  to navigate the medical instrument system  104  through anatomic passageways to a target location within a patient  103 . For example, the navigation stripe  799  can illustrate a “best” path through patient anatomy for the operator  105  to follow to deliver the distal portions  237  and/or  238  of the medical instrument  232  and/or of the elongate device  231 , respectively, to a target location within an anatomic region. In some embodiments, the navigation stripe  799  can be aligned with a centerline of or another line along (e.g., the floor of) a corresponding anatomic passageway. 
     In some embodiments, the virtual visualization system  115  can place the virtual camera within the anatomic model  796  at a position and orientation corresponding to the position and orientation of the image capture device  247  within the patient  103 . As further shown in  FIG.  12   , the virtual navigational image  792  illustrates virtual patient anatomy from substantially the same location at which the real navigational image  770  is captured by the image capture device  247 , e.g., showing carina  701  marking a branching point of two anatomic passageways  752  of the anatomic model  796 . Thus, the virtual navigational image  792  provides a rendered estimation of patient anatomy visible to the image capture device  247  at a given location within the anatomic region  350  of  FIG.  8   . Because the virtual navigational image  792  is based on the registration of a point cloud generated by the positional sensor system  108  and image data captured by the imaging system  118 , the correspondence between the virtual navigational image  792  and the real navigational image  770  provides insight regarding the accuracy and/or efficiency of the registration and can be used to improve the registration, as described in greater detail below. Furthermore, the real navigational images (e.g., the real navigational images  570  and  770 ) captured by the endoscopic imaging system  109  can (a) provide information regarding the position and orientation of the medical instrument system  104  within the patient  103 , (b) provide information regarding portions of an anatomic region actually visited by the medical instrument system, and/or (c) help identify patient anatomy (e.g., branching points or carinas of anatomic passageways) proximate the medical instrument system  104 , any one or more of which can be used to improve the accuracy and/or efficiency of the registration as described in greater detail below. 
     EXAMPLES 
     Several aspects of the present technology are set forth in the following examples. Although several aspects of the present technology are set forth in examples directed to systems, computer-readable mediums, and methods, any of these aspects of the present technology can similarly be set forth in examples directed to any of systems, computer-readable mediums, and methods in other embodiments. 
     In some embodiments in accordance with the present technology (example 1), a system for mitigating oversampling of data points includes a medical device comprising a sensor, wherein the medical device is insertable in an anatomic passageway of a patient such that the sensor is operable to detect one or both of a position and a motion of the medical device when inserted in the anatomic passageway; and a computing device in communication with the medical device, the computing device comprising a processor, and a memory coupled to the processor and storing instructions that, when executed by the processor, cause the system to perform operations comprising: receiving data points detected by the sensor of the medical device, the received data points associated with one or both of the detected position and the detected motion of the medical device; analyzing a set of the received data points to determine a motion parameter associated with a movement or change in position of the sensor of the medical device in a region of the anatomic passageway, wherein the motion parameter includes a change of one or both of a translational motion and a rotational motion of the sensor; comparing the motion parameter to a threshold to determine whether to accept the set of data points when the motion parameter satisfies the threshold or to reject the set of data points when the motion parameter does not satisfy the threshold; and recording the accepted set of data points in a survey point cloud usable to register the medical device in an anatomic frame of reference space. 
     Example 2 includes the system of any of examples 1, 3, 4 or 5 wherein the sensor is configured to generate one or both of position sensor data and motion sensor data during data sampling of the anatomic passageway of the patient, wherein the position sensor data is associated with one or more positions of the medical device within the anatomic passageway, and wherein the motion sensor data is associated with one or both of the translational motion and the rotational motion of the medical device within the anatomic passageway. 
     Example 3 includes the system of any of examples 1, 2, 4 or 5 wherein the change of one or both of the translational motion and rotational motion of the sensor includes a change in one or more of (i) a roll value, (ii) a pitch value, or (iii) a yaw value. 
     Example 4 includes the system of any of examples 1, 2, 3 or 5 wherein the threshold includes a motion value or a range of motion values associated with the one or both of the translational motion and the rotational motion of the sensor. 
     Example 5 includes the system of any of examples 1, 2, 3, or 4 wherein the system is configured to perform further operations include generating a registration between the accepted set of data points in the survey point cloud and image data points derived from a previously-acquired image of the anatomic passageway of the patient. 
     In some embodiments in accordance with the present technology (example 6), a system for mitigating oversampling of data points includes a medical device comprising a sensor, wherein the medical device is insertable in an anatomic passageway of a patient such that the sensor is operable to detect one or both of a position and a motion of the medical device when inserted in the anatomic passageway; and a computing device in communication with the medical device, the computing device comprising a processor, and a memory coupled to the processor and storing instructions that, when executed by the processor, cause the system to perform operations comprising: receiving data points detected by the sensor of the medical device, the received data points associated with a detected position of the medical device; analyzing the received data points to determine a distance parameter associated with a distance between a data point and one or more nearest neighbors of the data point; comparing the distance parameter to a threshold to determine whether to accept the data point among the received data points when the distance parameter satisfies the threshold or to reject the data point among the received data points when the distance parameter does not satisfy the threshold; and recording accepted data points in a survey point cloud usable to register the medical device in an anatomic frame of reference space. 
     Example 7 includes the system of any of examples 6, 8, 9 or 10 wherein the threshold includes a distance value or a range of distance values. 
     Example 8 includes the system of any of examples 6, 7, 9 or 10 wherein the received data points are initially recorded in the survey point cloud, and the recording the accepted data points in the survey point cloud includes deleting rejected data points that do not satisfy the threshold. 
     Example 9 includes the system of any of examples 6, 7, 8 or 10 wherein the system is configured to perform further operations that include storing the received data points in a temporary storage, and deleting rejected data points that do not satisfy the threshold from the temporary storage. 
     Example 10 includes the system of any of examples 6, 7, 8 or 9 wherein the system is configured to perform further operations include generating a registration between the recorded non-rejected data points in the survey point cloud and image data points derived from a previously-acquired image of the anatomic passageway of the patient. 
     In some embodiments in accordance with the present technology (example 11), a system for mitigating oversampling of data points includes a medical device comprising a sensor, wherein the medical device is insertable in an anatomic passageway of a patient such that the sensor is operable to detect one or both of a position and a motion of the medical device when inserted in the anatomic passageway; and a computing device in communication with the medical device, the computing device comprising a processor, and a memory coupled to the processor and storing instructions that, when executed by the processor, cause the system to perform operations comprising: receiving data points detected by the sensor of the medical device, the received data points associated with a detected position of the medical device; analyzing the received data points to determine a density parameter associated with a density of one or more data points to nearest neighbors data points; comparing the density parameter to a threshold to determine whether to accept the one or more data points among the analyzed data points when the density parameter satisfies the threshold or to reject the one more data points when the density parameter does not satisfy the threshold; and recording accepted data points in a survey point cloud usable to register the medical device in an anatomic frame of reference space. 
     Example 12 includes the system of any of examples 11, 13, 14 or 15 wherein the threshold includes a density value or a range of density values. 
     Example 13 includes the system of any of examples 11, 12, 14 or 15 wherein the received data points are initially recorded in the survey point cloud, and the recording the accepted data points in the survey point cloud includes deleting rejected data points that do not satisfy the threshold. 
     Example 14 includes the system of any of examples 11, 12, 13 or 15 wherein the system is configured to perform further operations that include storing the received data points in a temporary storage, and deleting rejected data points that do not satisfy the threshold from the temporary storage. 
     Example 15 includes the system of any of examples 11, 12, 13 or 14 wherein the system is configured to perform further operations that include generating a registration between the recorded non-rejected data points in the survey point cloud and image data points derived from a previously-acquired image of the anatomic passageway of the patient. 
     In some embodiments in accordance with the present technology (example 16), a system for mitigating oversampling of data points includes a medical device comprising a sensor, wherein the medical device is insertable in an anatomic passageway of a patient such that the sensor is operable to detect one or both of a position and a motion of the medical device when inserted in the anatomic passageway; and a computing device in communication with the medical device, the computing device comprising a processor, and a memory coupled to the processor and storing instructions that, when executed by the processor, cause the system to perform operations comprising: receiving data points detected by the sensor of the medical device, the received data points associated with a detected position of the medical device; analyzing the received data points to determine a density parameter associated with a density of one or more data points to nearest neighbors data points; comparing the density parameter to a threshold to determine whether to alter a weighting value of the one or more data points within the analyzed data points; when the density parameter meets the threshold, altering the weighting value of the one or more data points; and recording the data points to register the medical device in an anatomic frame of reference space. 
     Example 17 includes the system of any of examples 16, 18, 19 or 20 wherein the threshold includes a density value or a range of density values. 
     Example 18 includes the system of any of examples 16, 17, 19 or 20 wherein the altering the weighting value includes normalizing the weighting values. 
     Example 19 includes the system of any of examples 16, 17, 18 or 20 wherein the system is configured to perform further operations that include generating a registration between the recorded non-rejected data points in the survey point cloud and image data points derived from a previously-acquired image of the anatomic passageway of the patient. 
     Example 20 includes the system of any of examples 16, 17, 18 or 19 wherein the anatomic passageway includes pulmonary airway passages of lungs. 
     CONCLUSION 
     The above detailed descriptions of embodiments of the technology are not intended to be exhaustive or to limit the technology to the precise form disclosed above. Although specific embodiments of, and examples for, the technology are described above for illustrative purposes, various equivalent modifications are possible within the scope of the technology, as those skilled in the relevant art will recognize. For example, while steps are presented in a given order, alternative embodiments can perform steps in a different order. Furthermore, the various embodiments described herein can also be combined to provide further embodiments. 
     Implementations of the subject matter and the functional operations described in this patent document can be implemented in various systems, digital electronic circuitry, or in computer software, firmware, or hardware, including the structures disclosed in this specification and their structural equivalents, or in combinations of one or more of them. Implementations of the subject matter described in this specification can be implemented as one or more computer program products, i.e., one or more modules of computer program instructions encoded on a tangible and non-transitory computer readable medium for execution by, or to control the operation of, data processing apparatus. The computer readable medium can be a machine-readable storage device, a machine-readable storage substrate, a memory device, a composition of matter effecting a machine-readable propagated signal, or a combination of one or more of them. The term “data processing unit” or “data processing apparatus” encompasses all apparatus, devices, and machines for processing data, including by way of example a programmable processor, a computer, or multiple processors or computers. The apparatus can include, in addition to hardware, code that creates an execution environment for the computer program in question, e.g., code that constitutes processor firmware, a protocol stack, a database management system, an operating system, or a combination of one or more of them. 
     A computer program (also known as a program, software, software application, script, or code) can be written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment. A computer program does not necessarily correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, sub programs, or portions of code). A computer program can be deployed to be executed on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network. 
     The processes and logic flows described in this specification can be performed by one or more programmable processors executing one or more computer programs to perform functions by operating on input data and generating output. The processes and logic flows can also be performed by, and apparatus can also be implemented as, special purpose logic circuitry, e.g., an FPGA (field programmable gate array) or an ASIC (application specific integrated circuit). 
     Processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processor will receive instructions and data from a read only memory or a random access memory or both. The essential elements of a computer are a processor for performing instructions and one or more memory devices for storing instructions and data. Generally, a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data, e.g., magnetic, magneto optical disks, or optical disks. However, a computer need not have such devices. Computer readable media suitable for storing computer program instructions and data include all forms of nonvolatile memory, media and memory devices, including by way of example semiconductor memory devices, e.g., EPROM, EEPROM, and flash memory devices. The processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry. 
     From the foregoing, it will be appreciated that specific embodiments of the technology have been described herein for purposes of illustration, but well-known structures and functions have not been shown or described in detail to avoid unnecessarily obscuring the description of the embodiments of the technology. To the extent any materials incorporated herein by reference conflict with the present disclosure, the present disclosure controls. Where the context permits, singular or plural terms can also include the plural or singular term, respectively. Moreover, unless the word “or” is expressly limited to mean only a single item exclusive from the other items in reference to a list of two or more items, then the use of “or” in such a list is to be interpreted as including (a) any single item in the list, (b) all of the items in the list, or (c) any combination of the items in the list. As used herein, the phrase “and/or” as in “A and/or B” refers to A alone, B alone, and both A and B. Where the context permits, singular or plural terms can also include the plural or singular term, respectively. Additionally, the terms “comprising,” “including,” “having” and “with” are used throughout to mean including at least the recited feature(s) such that any greater number of the same feature and/or additional types of other features are not precluded. 
     Furthermore, as used herein, the term “substantially” refers to the complete or nearly complete extent or degree of an action, characteristic, property, state, structure, item, or result. For example, an object that is “substantially” enclosed would mean that the object is either completely enclosed or nearly completely enclosed. The exact allowable degree of deviation from absolute completeness may in some cases depend on the specific context. However, generally speaking the nearness of completion will be so as to have the same overall result as if absolute and total completion were obtained. The use of “substantially” is equally applicable when used in a negative connotation to refer to the complete or near complete lack of an action, characteristic, property, state, structure, item, or result. 
     From the foregoing, it will also be appreciated that various modifications can be made without deviating from the technology. For example, various components of the technology can be further divided into subcomponents, or various components and functions of the technology can be combined and/or integrated. Furthermore, although advantages associated with certain embodiments of the technology have been described in the context of those embodiments, other embodiments can also exhibit such advantages, and not all embodiments need necessarily exhibit such advantages to fall within the scope of the technology. Accordingly, the disclosure and associated technology can encompass other embodiments not expressly shown or described herein.