Source: https://patents.google.com/patent/JP2015116488A/en
Timestamp: 2020-05-30 23:03:40
Document Index: 735731481

Matched Legal Cases: ['art 12', 'art 12', 'art 12', 'art 12', 'art 12', 'art 12', 'Application No. 13']

JP2015116488A - Dynamic feature rich anatomical reconstruction from point cloud - Google Patents
Dynamic feature rich anatomical reconstruction from point cloud Download PDF
JP2015116488A
JP2015116488A JP2014254841A JP2014254841A JP2015116488A JP 2015116488 A JP2015116488 A JP 2015116488A JP 2014254841 A JP2014254841 A JP 2014254841A JP 2014254841 A JP2014254841 A JP 2014254841A JP 2015116488 A JP2015116488 A JP 2015116488A
JP2014254841A
JP6466159B2 (en
アサフ・マーション
Merschon Asaf
ファディ・マサルワ
2013-12-18 Priority to US14/132,631 priority Critical patent/US9265434B2/en
2013-12-18 Priority to US14/132,631 priority
2014-12-17 Application filed by バイオセンス・ウエブスター・（イスラエル）・リミテッドＢｉｏｓｅｎｓｅ Ｗｅｂｓｔｅｒ （Ｉｓｒａｅｌ）， Ｌｔｄ．, Biosense Webster (Israel) Ltd, バイオセンス・ウエブスター・（イスラエル）・リミテッドＢｉｏｓｅｎｓｅ Ｗｅｂｓｔｅｒ （Ｉｓｒａｅｌ）， Ｌｔｄ． filed Critical バイオセンス・ウエブスター・（イスラエル）・リミテッドＢｉｏｓｅｎｓｅ Ｗｅｂｓｔｅｒ （Ｉｓｒａｅｌ）， Ｌｔｄ．
2015-06-25 Publication of JP2015116488A publication Critical patent/JP2015116488A/en
2019-02-06 Publication of JP6466159B2 publication Critical patent/JP6466159B2/en
239000008264 clouds Substances 0 title claims abstract description 34
PROBLEM TO BE SOLVED: To perform three-dimensional heart reconstruction. Three-dimensional heart reconstruction is performed by performing cardiac catheterization using a probe having mapping electrodes, acquiring electrical data from respective locations within a region of interest in the heart, Display the location of dynamic data as a point cloud, reconstruct a heart model from the point cloud, apply a set of filters to the model to create a filtered volume, and divide the filtered volume Defining the components of the heart and notifying the divided and filtered volume. [Selection] Figure 1
The present invention relates to medical imaging. More specifically, the present invention relates to reconstruction of anatomical structures from relatively sparse data.
Today, medical catheterization is routinely performed, for example, in the case of arrhythmias such as atrial fibrillation, where regions of heart tissue abnormally conduct electrical signals to adjacent tissues, It blocks the normal cardiac cycle and causes aperiodic rhythms. The procedure for treating arrhythmia includes a step of surgically shutting off a signal source causing arrhythmia, and a step of shutting off a transmission path of such a signal. Stopping or altering the propagation of unwanted electrical signals from one part of the heart to another by selectively ablating heart tissue by applying energy, eg, radio frequency energy, through a catheter It may be possible. This ablation process destroys undesirable electrical pathways by creating a non-conductive damaged site. In such a procedure, it is desirable to provide the operator with a convenient image of the anatomy of the heart.
For example, although every left atrium has a similar basic shape, the left atrium is a complex three-dimensional structure whose walls have different dimensions from person to person. The left atrium can be divided into a number of substructures such as pulmonary veins, mitral or bicuspid valves, and the diaphragm that can be easily identified conceptually. These substructures also typically vary from person to person, but for the entire left atrium, each substructure has the same basic shape. In addition, a given substructure has the same relationship to other substructures of the heart, regardless of individual differences in the shape of the substructure.
Sparse data collection, known as “point clouds”, can be performed by the imaging system during medical catheterization, typically in conjunction with a coordinate system. Disclosed herein is a method and system for generating a multifunctional three-dimensional anatomical reconstruction from a point cloud, eg, a point cloud obtained from the heart or a portion thereof. This point cloud may be relatively sparse.
When using point clouds to reconstruct a three-dimensional model of the heart, there is a problem with the proper resolution of the reconstruction. A low resolution provides a coarse reconstruction, but works well even with low density point clouds. High resolution provides a much more versatile reconstruction, but is prone to error when applied to low density point clouds (holes and unconnected floating elements). This can be overcome by manually setting different resolutions in different areas of the reconstruction. However, the manual process is uncomfortable and time consuming. An approach to automation is desired.
In accordance with an embodiment of the present invention, a method for three-dimensional reconstruction of the heart is provided, the method comprising inserting a probe having a mapping electrode into the heart of a living subject and applying the mapping electrode to a plurality of heart concerns. Energizing to be in contact with the tissue within the region, obtaining electrical data from each location within the region of interest, displaying the location of the electrical data as a point cloud, and point cloud Reconstructing a heart model from, applying a set of filters to the model to create a filtered volume, dividing the filtered volume to define heart components, and dividing and filtering And at least one of the above steps is embodied in a computer-readable non-transitory storage medium. It is performed in hardware or computer software.
According to one aspect of the method, reconstructing the model and applying the set of filters is performed repeatedly using a portion of the point cloud until a stop condition is met. The stop condition is one of a failure to achieve progressive resolution enhancement of the filtered volume in a predetermined number of iterations, expiration of a preset time interval, completion of a predetermined number of iterations. Can be included.
According to an additional aspect of the invention, applying the set of filters includes applying a respective subset of the set of filters in successive iterations of applying the set of filters.
According to another aspect of the invention, the subset is selected randomly.
According to yet another aspect of the invention, the subset is selected based on a search strategy.
According to a further aspect of the invention, applying the set of filters has a resolution in which the filtered volume exceeds the resolution of the filtered volume in the previous iteration of applying the set of filters. Using the filtered volume as an input to a subsequent iteration of resolving and remodeling the model and applying a set of filters in response to the determination.
A further aspect of the invention is to divide the filtered volume and then store each realized value of the divided and filtered volume and combine the realized value of the divided and filtered volume into a composite volume. And displaying the composite volume.
In accordance with an embodiment of the present invention, there is further provided an apparatus for performing the method described above.
For a better understanding of the present invention, reference is made by way of example to the detailed description of the invention, which should be read in conjunction with the following drawings, in which like elements have like reference numerals.
1 is an illustration of a system for a cardiac catheter of a living subject constructed and operative in accordance with an embodiment of the present invention. FIG. It is a figure which shows the sparse point cloud of the data of the heart acquired from each site | part based on embodiment of this invention. 4 is a flowchart of a method for three-dimensional anatomical reconstruction from a point cloud, according to an embodiment of the present invention. 6 is a series of charts illustrating stages in volume reconstruction from a point cloud, according to an embodiment of the present invention.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the various principles of the present invention. However, it will be apparent to those skilled in the art that these details are not necessarily all required for practice of the invention. In this case, well known circuitry, control logic, and details of computer program instructions for conventional algorithms and processes are not shown in detail in order not to unnecessarily obscure the general concepts.
Aspects of the invention may be embodied in the form of software programming code, typically maintained in permanent memory such as a computer readable medium. In a client / server environment, such software programming code is stored on the client or server. The software programming code may be embodied on any of a variety of known non-transitory media for use with a data processing system, such as a diskette, hard drive, electronic media, or CD-ROM. it can. The code can be distributed on such media, or a storage device on another system for use by a user of another computer system over a certain network from a memory or storage device of one computer system Can be distributed.
Turning now to the drawings and referring first to FIG. 1, this FIG. 1 is a diagnostic or therapeutic procedure for a heart 12 of a living subject constructed and operated in accordance with the disclosed embodiments of the present invention. 1 is an explanatory diagram of a system 10 for performing a physical procedure. FIG. The system includes a catheter 14 that is inserted percutaneously by an operator 16 through the subject's vasculature and into the chamber or vasculature of the heart 12. An operator 16, typically a physician, contacts the distal tip 18 of the catheter with the ablation target site on the heart wall. If necessary, U.S. Patent Nos. 6,226,542 and 6,301,496, the disclosures of which are incorporated herein by reference, and U.S. Patent Nos. Assigned to the same assignee as the present application. Based on the method disclosed in US Pat. No. 6,892,091, an electrical activity map can be generated. One commercially available product that embodies each element of the system 10 is Biosense Webster, Inc. (3333 Diamond Canyon Road, Diamond Bar, CA 91765) is available as a CARTO® 3 system. This system can be modified by one of ordinary skill in the art to embody the principles of the invention described herein.
For example, the region determined to be abnormal by the evaluation of the electrical activity map is caused by, for example, flowing a high-frequency current through one or more electrodes of the distal tip 18 that applies high-frequency energy to the myocardium through a wire in the catheter. Ablation can be achieved by applying energy. This energy is absorbed into the tissue and heats it to the extent that it permanently loses its electrical excitability (typically about 50 ° C.). If performed without hindrance, the surgery creates a non-conductive lesion site in the heart tissue that blocks the abnormal electrical pathway that causes the arrhythmia. Many different cardiac arrhythmias can be treated by applying the principles of the present invention to different heart chambers.
The catheter 14 typically includes a handle 20 having suitable controls that allow the operator 16 to turn, position, and orient the distal end of the catheter as needed to perform ablation. . To assist the operator 16, the distal portion of the catheter 14 contains a position sensor (not shown) that provides a signal to a processor 22 disposed within the console 24.
Ablation energy and electrical signals are delivered to / from the heart 12 via a cable 34 leading to the console 24 through one or more ablation electrodes 32 disposed at or near the distal tip 18. 12 can be transported. Pacing signals and other control signals can be conveyed from the console 24 through the cable 34 and electrode 32 to the heart 12. The sensing electrode 33 is similarly connected to the console 24 and is disposed between the ablation electrodes 32 and has a connection to the cable 34.
Console 24 is connected to body surface electrode 30 and other components of the positioning subsystem by wire connection 35. Electrode 32 and body surface electrode 30 measure tissue impedance at the ablation site as taught in US Pat. No. 7,536,218 issued to Govari et al., Incorporated herein by reference. Can be used for. A temperature sensor, such as a thermocouple 31, can be mounted on or near the ablation electrode 32 and, if necessary, near the sensing electrode 33.
The console 24 typically houses one or more ablation power generators 25. The catheter 14 can be adapted to deliver ablation energy to the heart using any well-known ablation technique such as, for example, radio frequency energy, ultrasound energy, and laser-generated light energy. Such methods are described in US Pat. Nos. 6,814,733, 6,997,924, and 7,156, assigned to the same assignee as the present application, which are incorporated herein by reference. No. 816.
The processor 22 functions as an element of the positioning subsystem in the system 10 that measures the position and orientation coordinates of the catheter 14. The processor 22 has an additional imaging processing function, which will be described below.
In one embodiment, the positioning subsystem uses the magnetic field generating coil 28 to generate magnetic fields within a predetermined working volume and to sense the position and orientation of the catheter 14 by sensing these magnetic fields at the catheter. Including an arrangement of magnetic position tracking to determine; The positioning subsystem can use, for example, impedance measurements taught in US Pat. No. 7,756,576, which is incorporated herein by reference, and US Pat. No. 7,536,218 described above. .
As described above, the catheter 14 is coupled to the console 24 so that the operator 16 can observe and adjust the function of the catheter 14. Console 24 includes a processor, preferably a computer with suitable signal processing circuitry. The processor is coupled to drive the monitor 29. The signal processing circuit generally receives, amplifies, and amplifies signals from the catheter 14, including signals generated by the above-described sensors and a plurality of position sensing electrodes (not shown) disposed distally of the catheter 14. Filter and digitize. The digitized signals are received and used by the console 24 and positioning system to calculate the position and orientation of the catheter 14 and to analyze the electrical signals from the electrodes.
Although not shown in the figures for simplicity, the system 10 typically includes other elements. For example, the system 10 can include an electrocardiogram (ECG) monitor that is coupled to receive signals from one or more body surface electrodes to provide an ECG synchronization signal to the console 24. Is done. Also, as described above, the system 10 is also typically an externally applied reference patch attached to the outside of the subject's body, or the body 12 inserted into the heart 12 and maintained in a fixed position relative to the heart 12. A reference position sensor is also included in any of the catheters disposed in the. Conventional pumps and lines are provided in the catheter 14 to circulate through the liquid to cool the ablation site.
Reference is made to FIG. 2, which is an illustration of a sparse point cloud 42 of heart data acquired from each site, in accordance with an embodiment of the present invention. Such a point cloud can be acquired by ultrasonic imaging of the ventricle. Alternatively, the position of data 44 is reported by a position sensor on the catheter, as is known in the art. For example, sparse data uses the fast anatomical mapping (FAM) function of the CARTO® 3 system in cooperation with a mapping catheter such as a NAVISTAR® Thermocool® catheter. These are all available from Boysense Webster, Inc. 3333 Diamond Canyon Road, Diamond Bar, CA 91765. A processor, such as found in a CARTO system, can be programmed by those skilled in the art to perform functions as described below.
Data 44 may be associated with coordinates in the respective three-dimensional space based on anatomical landmarks or fiducial marks using position information provided by position sensor 46 on catheter 48 shown in FIG. it can. The position information can be expressed with six degrees of freedom.
Reference is made to FIG. 3, which is a flowchart of a method for three-dimensional anatomical reconstruction from a point cloud, according to an embodiment of the present invention. In an initial step 51, a point cloud of the structure, such as the heart or a portion of it 42 (FIG. 3), is obtained using the system 10 (FIG. 1) or equivalent system functionality as described above.
Next, in step 53, the first volume reconstruction is prepared from the point cloud obtained in the first step 51. Note that initial steps 51 and 53 may be performed in the same or separate catheterization sessions. One way to perform step 53 is to associate data 44 with the center of the corresponding volume element or voxel (not shown) and perform the steps described below.
Referring to FIG. 4, this is a series of diagrams illustrating the steps of volume reconstruction from a point cloud according to an embodiment of the present invention. The processor 22 (FIG. 1) uses a mapping module to first connect points 57, eg, position 57 of the data 44 (FIG. 3), to define a mesh 61 of line segments 59.
The mesh 61 is not necessarily required, but is typically a triangular mesh. In one embodiment, processor 22 uses a ball pivot algorithm (BPA) to generate mesh 61. Typically, when BPA is used, the ball size is set to correspond to the voxel size described above. The Alternatively, the mesh 61 may be generated as a Delaunay triangulation that includes a plurality of triangles having vertices corresponding to the positions 57. Triangulation triangles may be based on a Voronoi diagram formed around position 57. However, the processor 22 may use any convenient method known in the art to form a mesh.
After creating the mesh 61, the processor 22 generates a generally smooth surface 63 connecting the position 57 and the line segment 59. To generate the surface 63, the processor 22 typically uses an interpolation method and additionally or alternatively uses an extrapolation method. In addition, to ensure that the surface 63 is generally smooth, the processor 22 may adjust the surface to be close to, but not necessarily including, some of the positions 57 and line segments 59. it can. As an example, the surface 63 has contour lines 65, 67, 69.
Then, after generating the surface 63, the processor 22 checks whether the surface is closed, that is, whether the surface is topologically equivalent to a closed surface such as a sphere. Typically, the surface 63 has one or more openings and is not closed. An opening in the surface 108 may represent a structure that occurs naturally in the organ, such as the superior or inferior vena cava of the right atrium. Such an opening is referred to herein as a natural opening. In addition, an opening, referred to herein as an artificial opening, may exist in the surface 63 because the organ is not fully mapped.
If surface 63 is not closed, processor 22 causes the surface to close by adding additional surface elements until the surface closes. The surface created by closing the surface 63 is referred to herein as the closed surface 71. In one embodiment, the opening is closed by adding an oriented bounding box surrounding the opening, the box having a minimum volume. This box is then treated as part of the surface.
This closed surface 71 is defined as:
S 1 (X, Y, Z) = 0 Eq. (1),
Where S 1 is a function. The closed surface 71 surrounds a volume 73 that contains the voxels 75. Volume 73 is also referred to herein as volume V 1 and can be defined as follows:
V 1 = {V (x, y, z) | S 1 (x, y, z) <0} Eq. (2),
Here, V (x, y, z) indicates a voxel centered at (x, y, z), and V 1 is a volume formed by the voxel 75.
Returning to FIG. 3, the process continues from step 77. Volume 73 (FIG. 4) is subject to one set of filter functions F. Some filter functions F may be applied to the mesh 61 and others to the volume 73. A typical list of filter functions is described below.
f1: Given a mesh, calculate a mesh genus G for Euler's graph invariant characteristic χ well known in the field of topology, and return to whether G == 1. If G == 1, there is a hole in the mesh.
f2: Given a mesh, check how many (n) multi-connection elements there are and return to n == 1. If n == 1, the mesh is composed of at least two discrete elements. This is inconsistent with an anatomical structure that would correspond to a mesh with only one element, ie a single connected mesh.
f3: Given a mesh, look for vertices with maximum discrete Gaussian curvature K in the reconstructed mesh. The Gaussian curvature K can be calculated using the following Gaussian curvature operator:
Here theta j is the j-th surface, the angle at the vertex x i, # f represents the number of vertices x i surrounding surface. A Mixed is the vertex x i .
Is a mixed region in the mesh around. Discrete Gaussian curvature K is described in the publication Discrete Differential-Geometrically Operators for Triangulated 2-Manifolds, Mark Meyer et al., International Workshop on Visualization.
Then, it is determined whether the maximum value of delta K indicating the change in Gaussian curvature K in successive mesh divisions is smaller than the specified threshold value. This gives an indication of the smoothness of the mesh.
f4: Calculate the skeleton of a predetermined mesh and confirm that it has no contact. The presence of a contact indicates that the mesh has an appendage and thus requires further division iterations. A method for forming a skeleton graph of a mesh is described in, for example, the literature Skelton Extraction by Mesh Construction, Oskar Kin-Chun Au et al., ACM Trans. on Graph, vol. 27, no. 3, pp. 44: 1-44: 10, 2008.
f5: Run the tube-oriented segmentation algorithm S (for searching for cylindrical elements) and check whether the number of elements is equal to, greater than or equal to the specified number. Hierarchical body segmentation algorithms are suitable and are described, for example, in the literature Mesh Segmentation Using Feature Point and Core Extraction, Sagi Katz et al., The Visual Computer, Vol. 21, no. 8-10. (September 2005), pp. 649-658, the contents of which are incorporated herein by reference.
Preferably all filters F should be used. However, for some applications, a subset of filter F may be sufficient, and the subset saves computer resources. In different iterations of step 77, various subsets of the filter F can be selected. In various cardiac applications, subsets may be selected according to an empirically created order in order to improve the mesh most rapidly. Alternatively, the subset may be selected at random, or the operator may instruct. Alternatively, the set of filters F may be treated as a search space, and subsets can be selected based on search strategies and methods known in the art of optimization. For example, subsets can be selected in the following order: {f1, f2, f3, f5}, {f1, f2, f3}, {f1, f2, f5}, {f1, f2}, {f1, f2, f3, f4, f5}, {f1, f2, f3, f4}, {f1, f2, f4, f5} and {f1, f2, f4}. Based on the progress achieved in the previous iteration of step 77, the selection of the set can be automatically established at any given iteration. Typically, the quality of the result is correlated with the number of filters used.
Next, at decision step 79, the mesh is a “good mesh” at the current resolution, ie (1) the mesh meets some predetermined criteria or has a predetermined quality, and (2 It is determined whether the mesh has a higher resolution than that of the last iteration.
Each filter F has its own figure of merit that informs the quality of the results. The criteria applied to the evaluation of the filter results vary from application to application, and therefore the criteria are selected by the user. For example, a combination of figure of merit may be created. Alternatively, the result of the minimum set of filters F must reach or exceed the respective criterion. Many combinations of each criterion for filter F may be created. For Gaussian curvature, the choice of a value between 2 * PI and 1.5 * PI is common. In another example, selection of 0 is common for a seed value filter (Euler's method).
In general, the quality of the results correlates with the number of filters used.
If the decision at decision step 79 is affirmative, the control operation returns to step 53 to attempt to obtain a better resolution, and a subset of the raw point cloud associated with the currently ongoing divided portion is obtained. Performed by reference, reconstruct the volume as described above and repeat the filtering operation. Optionally, additional interpolation points on the surface 63 may be added between the positions 57.
If the determination at step 79 is negative, the current reconstruction value is discarded at step 89 and the method continues using the result of the previous iteration.
Here, the control operation proceeds to determination step 81 where it is determined whether or not the stop condition is satisfied. If the stop condition is not met, the control operation returns to step 53 to improve the quality of the current reconstructed volume. Typical stop conditions include failure to progress in a predetermined number of iterations, expiration of a preset time interval, or completion of a predetermined number of iterations.
If the stop condition is not satisfied in decision step 81, the reconstructed volume is divided in step 83. The segmentation algorithm does not require operator intervention to identify heart segments. A plummer algorithm involving shape partitioning into tubular portions is suitable for use in step 83. This algorithm is described in the document Mesh Segmentation-A Computational Study, M.M. Atten et al., Proceedings of the IEEE International Conference on Shape Modeling and Applications 2006, the contents of which are incorporated herein by reference. Other segmentation algorithms known in the art can also be used.
The current divided volume represents the best result so far obtained. This is stored in step 87.
At decision step 93, it is determined whether there are any encircled points to be processed. If the determination is affirmative, the control operation returns to step 53. It is desirable to repeat starting from step 53 using other points enclosed within the mesh and the relevant part of the raw point cloud (rather than the entire point cloud as in the first iteration). .
If the determination in decision step 93 is negative, the control operation proceeds to step 91. The volumes stored in step 87 are now combined into a single composite mesh. This step can be accomplished using the teachings of Application No. 13 / 669,511 having the title “Combining Three-Dimensional Surfaces” assigned to the same assignee as the present application, the contents of which are incorporated herein by reference. The synthesized surface provides a more complete 3D model than any individual mesh without loss of accuracy.
When step 91 is completed, the composite mesh is output to the display in the final step 85.
Those skilled in the art will recognize that the present invention is not limited to what has been particularly shown and described hereinabove. Rather, the scope of the present invention is intended to cover non-prior art variations and modifications that would occur to those of ordinary skill in the art upon reading the above described combinations of different characteristics and some combinations, as well as the foregoing description. Is also included.
Inserting a probe having a mapping electrode into the heart of a living subject;
Biasing the mapping electrode into contact with tissue within a plurality of regions of interest of the heart;
Obtaining electrical data from respective positions within the region of interest;
Displaying the position of the electrical data as a point cloud;
Reconstructing the heart model from the point cloud;
Applying a set of filters to the model to create a filtered volume;
Dividing the filtered volume to define components of the heart;
Informing said divided and filtered volume, wherein at least one of said steps is performed in computer hardware or computer software embodied in a computer-readable non-transitory storage medium .
(2) The method according to embodiment 1, wherein the step of reconstructing the model and the step of applying the set of filters are repeatedly performed using a part of the point cloud until a stop condition is satisfied. Method.
3. The method of embodiment 2, wherein applying the set of filters comprises applying a respective subset of the set of filters in successive iterations of applying the set of filters.
(4) The method of embodiment 3, wherein the subset is selected randomly.
5. The method of embodiment 3, wherein the subset is selected based on a search strategy.
(6) The stop condition includes failure to achieve progressive resolution enhancement of the filtered volume in a predetermined number of iterations, expiration of a preset time interval, and completion of the predetermined number of iterations. The method of embodiment 2, comprising one of them.
(7) The step of applying the set of filters is
Determining that the filtered volume has a resolution that exceeds the resolution of the filtered volume in a previous iteration of applying a set of filters;
Embodiment 2 comprising: using the filtered volume as an input to a subsequent iteration of reconfiguring the model and applying the set of filters in response to the determination. The method described.
(8) The method is
Storing each realized value of the divided and filtered volume after performing the step of dividing the filtered volume;
Combining the realized values of the divided and filtered volumes into a composite volume, wherein displaying the divided and filtered volume comprises displaying the composite volume The method according to embodiment 7.
(9) A device,
A probe having a position sensor and electrodes at the distal portion and adapted to be inserted into contact with the heart of the subject's body;
A processor coupled to the position sensor,
Receiving electrical data from the electrodes when the probe is at a respective location within a region of interest of the heart;
A processor operable to perform the step of notifying the divided and filtered volume.
(10) The method according to embodiment 9, wherein the step of reconstructing the model and the step of applying the set of filters are repeatedly performed using a part of the point cloud until a stop condition is satisfied. apparatus.
11. The apparatus of embodiment 10, wherein applying the set of filters comprises applying a respective subset of the set of filters in successive iterations of applying the set of filters.
12. The apparatus of embodiment 11, wherein the subset is selected randomly.
The apparatus of claim 11, wherein the subset is selected based on a search strategy.
(14) the stop condition includes failure to achieve progressive resolution enhancement of the filtered volume in a given number of iterations, expiration of a preset time interval, and completion of a predetermined number of iterations; The apparatus of embodiment 10, comprising one of the following.
(15) applying the set of filters comprises:
11. The method of claim 10, comprising using the filtered volume as an input to a subsequent iteration of reconfiguring the model and applying the set of filters in response to the determination. The device described.
(16) The apparatus further comprises a display, and the processor
The step of combining the realization values of the divided and filtered volumes into a composite volume is operable to perform an additional step of notifying the divided and filtered volume, Embodiment 16. The apparatus of embodiment 15, comprising the step of displaying on the display.
The apparatus of claim 1, wherein reconstructing the model and applying the set of filters are performed repeatedly using a portion of the point cloud until a stop condition is met.
The apparatus of claim 2, wherein applying the set of filters comprises applying a respective subset of the set of filters in successive iterations of applying the set of filters.
The apparatus of claim 3, wherein the subset is selected randomly.
The apparatus of claim 3, wherein the subset is selected based on a search strategy.
The stopping condition includes: failure to achieve progressive resolution enhancement of the filtered volume in a given number of iterations; expiration of a preset time interval; and completion of a predetermined number of iterations. The apparatus of claim 2, comprising one.
Applying a set of filters
Using the filtered volume as an input to a subsequent iteration of reconfiguring the model and applying the set of filters in response to the determination. The device described.
The apparatus further comprises a display, and the processor
The step of combining the realization values of the divided and filtered volumes into a composite volume is operable to perform an additional step of notifying the divided and filtered volume, 8. The apparatus of claim 7, including the step of displaying a value on the display.
JP2014254841A 2013-12-18 2014-12-17 Dynamic reconstruction of multifunctional anatomy from point clouds Active JP6466159B2 (en)
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KR20150145950A (en) * 2014-06-20 2015-12-31 삼성전자주식회사 Method and apparatus for extracting feature regions in point cloud
US10588692B2 (en) 2015-11-06 2020-03-17 Biosense Webster (Israel) Ltd. Pulmonary vein isolation gap finder
US10398346B2 (en) 2017-05-15 2019-09-03 Florida Atlantic University Board Of Trustees Systems and methods for localizing signal resources using multi-pole sensors
US10398338B2 (en) * 2017-10-06 2019-09-03 Florida Atlantic University Board Of Trustees Systems and methods for guiding a multi-pole sensor catheter to locate cardiac arrhythmia sources
US10593112B1 (en) 2019-04-15 2020-03-17 Biosense Webster (Israel) Ltd. Chamber reconstruction from a partial volume
JP2012045256A (en) * 2010-08-30 2012-03-08 Fujifilm Corp Region dividing result correcting device, method and program
CN106725448B (en) * 2006-05-17 2020-01-31 圣朱德医疗有限公司房颤分公司 System and method for mapping electrophysiological information onto complex geometries
CN103021017B (en) * 2012-12-04 2015-05-20 上海交通大学 Three-dimensional scene rebuilding method based on GPU acceleration
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AU2014274615B2 (en) 2018-10-04
EP2886047A1 (en) 2015-06-24
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