Patent Description:
Substantial progress has been made towards increasing the effectiveness of medical treatment while reducing trauma and risks to the patient. Many procedures that once required open surgery now may be done with less invasive techniques, thus providing for less recovery time and risks of infection for the patient. Certain procedures requiring biopsy, electrostimulation, tissue ablation, or removal of native or foreign bodies may be performed through minimally-invasive surgery.

In the field of urology, for example, renal calculi or kidney stones can accumulate in the urinary tract and become lodged in the kidney. Kidney stones are deposits of materials from the urine, typically minerals and acid salts. While smaller stones may pass from the body naturally, larger stones can require surgical intervention for removal. While open surgery was once the standard treatment for the removal of stones, other less invasive techniques, such as ureteroscopy and percutaneous nephrolithotomy/nephrolithotripsy (PCNL), have emerged as safer, effective alternatives. Additionally, advances in imaging technology have improved a medical professional's ability to identify and locate stones before and during procedures. Nevertheless, medical professionals still must analyze images to determine the location of stones and whether any stones are present. Moreover, the images are often obstructed, blurry, and/or otherwise difficult to evaluate, making the medical professional's task of discerning the presence of any stones challenging. <CIT> discloses an ultrasound imaging system which includes an interface coupled to an ultrasound imaging component and configured to receive a plurality of image data frames representative of a subject's body including at least a portion of a lung; a processing component in communication with the interface and configured to determine a metric for each image data frame of the plurality of image data frames based on a threshold comparison; and determine a dynamic air bronchogram (AB) condition of the subject's body based on a variation across the metrics of the plurality of image data frames. <CIT> discloses an information obtaining apparatus capable of obtaining information about a blood vessel with high accuracy which includes a first unit configured to obtain three or more image data pieces different in imaging conditions, a second unit configured to obtain a first index value of a first region and a second index value of a second region, a third unit configured to select a pair of the image data pieces from the three or more image data pieces using the first index value and the second index value of the image data, and a fourth unit configured to obtain information about a blood vessel using the selected pair of the image data pieces. <CIT> discloses a method for automated image capture of a body tissue in situ, comprising: providing an imaging device configured to transmit an image stream of a body tissue; and using at least one hardware processor for: receiving the image stream, identifying a medical accessory appearing in the image stream, and capturing multiple images of the body tissue, wherein (i) at least one of the images is captured before said identifying, and (ii) at least one of the images is captured at one or more specified times upon said identifying. <CIT> discloses a method for depth mapping objects in a scene by an apparatus of a moving or movable platform, the method comprising: actively illuminating the scene with pulsed light that is generated by at least one pulsed light illuminator; receiving, responsive to illuminating the scene with the pulsed light, reflections on at least one image sensor that comprises a plurality of pixel elements; gating at least one of the plurality of pixel elements of the at least one image sensor for converting the reflections into pixel values for generating reflection-based image data descriptive of at least two depth-of-field (DOF) ranges and an overlapping DOF region; and determining, based on at least one first pixel value of a first DOF in the overlapping DOF region, and further based on at least one second pixel value of a second DOF in the overlapping DOF region, depth information of one or more objects located in the overlapping DOF region of the scene.

The systems, devices, and methods of the current disclosure may rectify some of the deficiencies described above, and/or address other aspects of the prior art.

Examples of the present disclosure relate to, among other things, medical systems and methods. Each of the examples disclosed herein may include one or more of the features described in connection with any of the other disclosed examples.

The claimed invention for which protection is sought is defined in appended independent claim <NUM>, with further embodiments of the claimed invention being described in the appended dependent claims.

In one example, the present disclosure includes a method for processing electronic images from a medical device comprise receiving a first image frame and a second image frame from a medical device, and determining a region of interest by subtracting the first image frame from the second image frame, the region of interest corresponding to a visual obstruction in the first image frame and/or second image frame. Image processing may be applied to the first image frame and/or second image frame based on a comparison between a first area of the first image frame corresponding to the region of interest and a second area of the second image frame corresponding to the region of interest, and the first image frame and/or second image frame may be provided for display to a user.

In another example, the present disclosure includes a system for processing electronic images from a medical device, the system comprising a data storage device storing instructions for processing electronic images, and a processor configured to execute the instructions to perform a method for processing electronic images. The method may comprise receiving a first image frame and a second image frame from a medical device, and determining a region of interest by subtracting the first image frame from the second image frame, the region of interest corresponding to a visual obstruction in the first image frame and/or second image frame. Image processing may be applied to the first image frame and/or second image frame based on a comparison between a first area of the first image frame corresponding to the region of interest and a second area of the second image frame corresponding to the region of interest, and the first image frame and/or second image frame may be provided for display to a user.

In another example, the present disclosure includes a non-transitory computer-readable medium storing instructions that, when executed by a computer, cause the computer to perform a method for processing electronic images from a medical device. The method may comprise receiving a first image frame and a second image frame from a medical device, and determining a region of interest by subtracting the first image frame from the second image frame, the region of interest corresponding to a visual obstruction in the first image frame and/or second image frame. Image processing may be applied to the first image frame and/or second image frame based on a comparison between a first area of the first image frame corresponding to the region of interest and a second area of the second image frame corresponding to the region of interest, and the first image frame and/or second image frame may be provided for display to a user.

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate various exemplary embodiments and together with the description, serve to explain the principles of the disclosure.

Examples of the present disclosure include systems and methods to facilitate, and improve the efficiency and safety of minimally-invasive surgeries. For example, aspects of the present disclosure may provide a user (e.g., a physician, medical technician, or other medical service provider) with the ability to more easily identify and, thus, remove kidney stones or other material from a patient's kidney or other organ. In some embodiments, for example, the present disclosure may be used in planning and/or performing a flexible ureteroscope procedure, with or without laser lithotripsy. Techniques discussed herein may also be applicable in other medical techniques, such as any medical technique utilizing an endoscope.

Reference will now be made in detail to examples of the present disclosure described above and illustrated in the accompanying drawings.

The terms "proximal" and "distal" are used herein to refer to the relative positions of the components of an exemplary medical device or insertion device. When used herein, "proximal" refers to a position relatively closer to the exterior of the body or closer to an operator using the medical device or insertion device. In contrast, "distal" refers to a position relatively further away from the operator using the medical device or insertion device, or closer to the interior of the body.

Both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the features, as claimed. As used herein, the terms "comprises," "comprising," or other variations thereof, are intended to cover a non-exclusive inclusion such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements, but may include other elements not expressly listed or inherent to such a process, method, article, or apparatus. Additionally, the term "exemplary" is used herein in the sense of "example," rather than "ideal. " As used herein, the terms "about," "substantially," and "approximately," indicate a range of values within +/- <NUM>% of a stated value.

<FIG> illustrates a medical system <NUM> that includes a medical device such as an endoscope or other medical imaging device/medical device <NUM>, a network <NUM>, user device(s) <NUM> that may include a display(s) <NUM> that may be viewed by a user/practitioner/physician/patient <NUM>, and server(s) <NUM> that may comprise a frame processor <NUM> and/or a template matcher <NUM>. The endoscope <NUM>, user device(s) <NUM>, and/or server <NUM> may be wire connected (as shown), wirelessly connected, or otherwise communicatively coupled. Alternatively, functionality of the server <NUM> may be performed on endoscope <NUM>, user device <NUM>, etc. The server <NUM>, endoscope <NUM>, and/or user device <NUM> may further comprise a single electronic device.

As shown in <FIG>, endoscope <NUM> may be an insertion device such as, for example, a ureteroscope (e.g., LithoVue™ Digital Flexible Ureteroscope by Boston Scientific Corp.

With endoscope <NUM> positioned within a patient, for example, through the patient's urethra to a patient's kidney, a retrieval device (not shown) may be inserted to retrieve and remove material such as, for example, a kidney stone, with or without using laser lithotripsy. The endoscope <NUM> may record and/or transmit image and/or video data when inserted into a patient, and may have a light or other imaging source that may act to display images of the interior of a patient's vessels, organs, etc. The endoscope <NUM> may further be equipped with a laser for performance of laser lithotripsy, which may be used to remove, break up, or otherwise destroy one or more organ obstructions, such as kidney stones.

Display <NUM> may be a single, or at least a dual display, with either multiple screens or multiple displays on one screen. In one example, one of the displays may show an image or images currently or previously obtained by endoscope <NUM>. The other display may show an image or video obtained from one or more additional imaging devices <NUM>, such as by X-ray, Magnetic Resonance Imaging, Computerized Tomography Scan, rotational angiography, ultrasound, or another appropriate internal imaging device. Alternatively, one of the displays <NUM> may show an image modified using one or more image enhancement techniques discussed herein, while another may display an unenhanced image. Alternatively, one of the displays <NUM> may show an image modified using one or more enhancement techniques discussed herein, while another of the displays <NUM> may show an image modified using one or more different enhancement techniques discussed herein.

The software or applications, may manipulate, process, and interpret received images from imaging device <NUM> to identify the presence, location, and characteristics of a kidney stone or other material. As will be discussed further herein, the frame processor <NUM> and/or template matching applications <NUM> may process and enhance received images from endoscope <NUM>.

The physician may insert endoscope <NUM> into a patient when performing a medical procedure such as a lithotripsy to remove a kidney stone. The display <NUM> may become partially or completely obscured by pieces of kidney stone or other floating particulate matter, for example, when illuminated by a light on the endoscope <NUM>. Additionally, a flash created by a laser or other light source emitted from the endoscope <NUM> may cause surgeons or technicians to lose track of the kidney stone or other object of the medical procedure. The difficulty in tracking the kidney stone or object of the procedure may increase the time of performing the medical procedure, may increase the rate of errors of the medical procedure, and may increase the cognitive load in maintaining visual track of the object.

<FIG> is a flow diagram of an exemplary method for processing medical images, according to aspects of the present disclosure. A source of video or image frames <NUM>, which may be any medical device, such as an endoscope <NUM> or imaging device <NUM>, may provide frames to signal in <NUM>. The frames may be provided to a frame handler <NUM>, which may store a plurality of frames. One or more frames <NUM> may be provided to a frame processor <NUM>, which may produce one or more processed frames <NUM>. The processed frames <NUM> may be provided to the signal out <NUM>, which may be shown on display <NUM>.

The signal in <NUM> may be a software handler that may transmit that a new frame has been received. The frame handler <NUM> may either directly send a frame via the signal out <NUM> to a display <NUM>, or it may send one or more frames to the frame processor <NUM>. As will be discussed elsewhere herein, the frame processor <NUM> may perform distraction reduction and/or template matching techniques. The frame handler <NUM> may also send the original frame to the display <NUM>, and also send a copy of the frame to the frame processor <NUM>. The processed frame <NUM> may be received and also forwarded to the display <NUM>. This may allow for the original frame to be displayed alongside the processed frame <NUM> at the display <NUM>. Alternatively, the frame handler <NUM> may send the source frame <NUM> to the frame processor <NUM>, and the frame processor may return a processed frame <NUM> that comprises a dual display of the original and enhanced frame. Accordingly, the processed frame <NUM> may be larger than the source frame. The frame processor <NUM> may further add buttons or other user interface elements to the processed frame <NUM>.

Although techniques discussed herein are discussed as happening on the frame processor <NUM>, which may be depicted as being located on a single device, any of the functions of the frame processor may be spread across any number of devices, for example, any of the devices depicted in system <NUM>. Further, one or more of the signal in <NUM>, frame handler <NUM>, and/or signal out <NUM> may be housed on one or more servers <NUM>, or any of the other devices pictured on system <NUM>.

<FIG> is a flow diagram of an exemplary method for distraction deduction, according to aspects of the present disclosure. A plurality of frames may be received from a frame source <NUM>. The frame source may comprise an endoscope <NUM> or other medical imaging device <NUM>. One or more frames may be accumulated at a color frame buffer <NUM> and/or a grayscale frame buffer <NUM>. A plurality of frames may be accumulated for comparison. By comparing multiple frames with each other, a background may be discerned and distinguished from a visual obstruction. The visual obstruction may be a reflection, glare, light source, piece of dust, debris, particle, piece of kidney or gall stone or other calculus, etc. The visual obstruction may also have an associated brightness or intensity that is beyond a threshold. Using techniques discussed herein, the visual obstruction may be identified as a region of interest, and may receive processing to remove or mitigate the extent or severity of the obstruction.

When a new frame is received from the frame source <NUM>, a copy may be stored in the color frame buffer <NUM> and/or the grayscale frame buffer <NUM>. Frames in the color frame buffer <NUM> may have a plurality of channels for a plurality of colors, for example, three channels for red, green and blue. A copy of the frame may be stored in grayscale frame buffer <NUM>. The grayscale frame buffer <NUM> and/or the color frame buffer <NUM> may be used to determine one or more regions of interest in the frame, which may comprise one or more visual obstructions.

A received color frame may be converted to grayscale for storage in the grayscale frame buffer <NUM>. Conversion may comprise combining two or more of the color channels to form a grayscale frame. This may be done, at least in part, because different color channels in color frames may disagree about whether there is a visual obstruction (e.g., light intensity beyond a threshold, piece of debris beyond a size threshold, etc.). A combined-channel frame might not have such disagreements, since there is only one channel, yet the information from the multiple channels may still be present in the combined-channel frame.

Alternatively, a region of interest may be identified without determining grayscale frames. Any color channel which reports a visual obstruction according to techniques discussed herein may be used to determine a region of interest, even if there is disagreement from other color channels about whether there is any region of interest.

The region of interest mask generator <NUM> may receive frames from the grayscale frame buffer <NUM> and/or the color frame buffer <NUM>. The region of interest mask generator <NUM> may determine areas (regions of interest) with intensity changes that may be removed from the presented frame. A plurality of received frames, which may be consecutive frames, may be compared, and the common features may be subtracted. For example, if a current frame <NUM> is being processed to determine a region of interest, it may be compared with preceding frame <NUM> and the subsequent/later frame <NUM>. Common features, or features that are determined to be similar within a predetermined threshold, of the frames may be subtracted from each other. Two processed frames may be generated, the first a subtraction of the prior frame <NUM> and the current frame <NUM>, and the second a subtraction of the subsequent frame <NUM> and the current frame <NUM>. The two processed frames may then be added to each other. Any objects remaining may be designated as region(s) of interest <NUM>.

The common features may be the background, and thus, after the subtraction, only objects moving more quickly than the background, such as pieces of debris and other visual obstructions, may remain. These one or more visual obstructions may be designated as a region of interest and a region of interest mask may be applied.

Visual obstructions may also be objects with a light intensity that is beyond a threshold. For example, a reflection of a light or laser beyond a brightness/intensity threshold may not come from a particle or other object moving near the endoscope, but rather may come from light reflecting off the kidney stone itself, vessel/tissue/organ wall, or some other object that may not subtract out from nearby frames. Thus, regions of interest may also or alternatively be designated for any region with a light intensity/brightness exceeding a predetermined threshold. By comparing nearby frames, before and/or after the frame receiving processing, this type of visual obstruction may be identified. For example, a current frame <NUM> may be the frame receiving processing. The current frame <NUM> may be compared to a frame prior in time <NUM> that did not have the intense light visual obstruction. The two frames may be subtracted to determine a first subtracted frame. The current frame <NUM> may then be compared to a frame afterwards in time <NUM> that did not have intense light visual obstruction. The two frames may be subtracted to determine a second subtracted frame. The two subtracted frames may then be added together to determine the region of interest mask. This process may be repeated with more frames from which subtractions are performed. Alternatively, the determination of the region of interest may be performed by only comparing the frame to be processed to one other frame.

The one or more frames may be provided with the identified one or more regions or interest <NUM> to the region of interest comparator <NUM>. Now that the region(s) of interest is determined, it may be analyzed relative to one or more color channels of the associated color version of the frame. At a first color channel, for example red, two or more frames may be analyzed. For example, the frame being processed <NUM> may be compared with prior frame <NUM> and subsequent frame <NUM>. Image characteristics may be compared of the determined regions of interest <NUM> across a plurality of respective frames. For example, image characteristics the region of interest <NUM> of the current frame <NUM> may be compared to the corresponding region of interest <NUM> of prior frame <NUM>. The region of interest <NUM> may cover the same area of the frame as the region of interest <NUM>. Image characteristics of the region of interest <NUM> of the current frame <NUM> may further be compared to the region of interest <NUM> of subsequent frame <NUM>. For example, the image characteristics compared may be brightness, intensity, amount of intensity change relative to other frames, deviation from average brightness across a predetermined number of frames, motion pattern, texture, intensity histogram, entropy, etc..

In one embodiment, the intensity of a color channel across multiple frames may be compared, and the lowest, median, or average intensity may be determined. For example, in the red channel, pixels, on average, in region of interest <NUM> may have an intensity of <NUM>, while region of interest <NUM> may have an intensity of <NUM>, and region of interest <NUM> may have an intensity of <NUM>. The plurality of frames may have a visual obstruction that is very dark or very bright. Accordingly, the median value of the intensity across multiple frames may be selected. The pixels of the region of interest with the median value may be made to replace the pixels of the region of interest of the current frame <NUM>. This determination may be made for the other color channels, for example green and blue. It is possible that the regions of interest on some color channels will be replaced with that of another frame, while the regions of interest on other color channels will remain uncorrected. The color channels may be processed in this manner until all channels have a processed region of interest, as necessary. In the example of <FIG>, region of interest <NUM> of subsequent frame <NUM> may replace the region of interest <NUM> of the current frame <NUM>, as shown in <FIG> as region of interest <NUM>-<NUM>. In this manner, a bright flash or dark obstruction in the current frame may be replaced to mitigate or eliminate the visual obstruction.

A possible side effect of replacing regions of interest, as described above, is that hard or artificial edges (halos) may appear around the replaced regions. This may distort the viewer's perception of the true shape of the object receiving image correction, and may give the viewer the impression of edges that are not actually present in the body of the patient.

To mitigate or eliminate this problem, after the region of interest is determined, at <NUM> an edge <NUM> of the region of interest may be determined. This edge <NUM> may be of a predetermined thickness, or may be based on the dimensions of the region of interest. For example, as the region of interest gets larger, the edge <NUM> may automatically be determined to be thicker. The edges may be determined using morphological operations (for example, dilation and erosion operations). The region of interest edge may be placed over the current frame <NUM> with the replaced region of interest <NUM>. The edge of the replaced region of interest <NUM> may be removed. The region of interest edge may be in-painted, or may have a color gradient from the inside edge to the outside edge applied such that the "halo" of the processed current frame is removed/smoothed out, and any harsh edges that may cause visual distraction are removed. The color gradient might not only be a first-degree gradient, but also a second derivative gradient to help smooth the color transition from the inside to the outside of the edge <NUM>. After these techniques are applied, a processed frame <NUM>, with corrected edge <NUM>, may be provided for display to a user.

<FIG> is a flow diagram of an exemplary method for determining a template for object tracking in medical images, according to aspects of the present disclosure. As discussed above, it may be difficult for an endoscope operator to track a target object or tissue, such as a kidney stone. In addition to visual obstructions, there is movement of the endoscope and other effects that may increase the tracking difficulty and thereby the cognitive load of the endoscope operator. While processing frames to reduce or remove visual obstructions may make the process easier, it may help to highlight or otherwise indicate the target tissue or object on the display automatically. For example, a box or outline may be placed around the target object, such as a kidney stone. <FIG> discloses techniques of template matching <NUM>, which may be performed separately from, or in addition to, distraction deduction techniques discussed elsewhere herein.

At frame <NUM> (<NUM>), the frame may be provided to a trained template system <NUM>. The trained template system <NUM> may have been trained with images of the target object, such as images of kidney stones. The trained template system may return a portion of frame <NUM> corresponding to the target object, for example, the portion of frame <NUM> containing an image of the kidney stone, indicated as template <NUM>. Template <NUM><NUM> may be used to quickly and automatically identify the same target object in subsequent frame <NUM> (<NUM>). For the given template and target frame, various image features may be determined (intensity, gradient, etc.) for both, which may be used to determine if a match exists. The target object in frame <NUM> may be somewhat different, as it may have rotated, changed shape (been fragmented), move closer or further from the camera, etc. That said, if template <NUM> matches any region of frame <NUM> within a predetermined tolerance/confidence threshold, the matching region may be assumed to be the target object in the subsequent frame. In this manner, using templates taken from prior frames, an object may be tracked across a plurality of frames. As discussed above, a bounding box, a circle, pointer, or any other indicator may be placed around the target object to allow for easier user tracking of the object. In addition, an indicator of the confidence of the match may also be determined and/or displayed.

A portion of frame <NUM> may be used to generate template <NUM>. Template <NUM> may be used to locate the target object in subsequent frame <NUM> (<NUM>). The portion of frame <NUM> containing the target object may be used to generate template <NUM>. Using templates may be faster and computationally less intensive than providing each frame to the trained template system <NUM> for tracking the target object. Accordingly, templates might be used preferentially, unless the target object cannot be tracked within a predetermined confidence. Template <NUM> may be used to recognize the target object in frame <NUM> (<NUM>).

The templates may be compared rapidly against each portion of the frame to determine if there is a match within a predetermined threshold or confidence. However, there might not be a match to within a predetermined threshold or confidence. For example, a kidney stone may be fragmented and be shaped substantially differently from one frame to the next. If, for example, the target object is not recognizable within a tolerance using a template from the prior frame, the frame, such as a frame <NUM>, may be provided again to the trained template system <NUM>. The trained template system <NUM> may return template <NUM>, which may be used to recognize the target object in frame <NUM> (<NUM>), and so on.

In addition, a buffer of templates may be stored from prior frames. If an object occludes the endoscope <NUM> or other medical imaging device, if only templates of the immediately prior frame were used to track the target object, tracking of the target object might quickly fail. In the event that the target object is not recognized within a predetermined confidence, additional prior templates may be analyzed to search for a match.

<FIG> is a flow diagram of an exemplary method for determining medical image enhancement, according to aspects of the present disclosure. At step <NUM>, a first image frame and a second image frame may be received from a medical imaging device. At step <NUM>, a region of interest may be determined by subtracting the first image frame from the second image frame, the region of interest corresponding to a visual obstruction in the first image frame and/or second image frame. At step <NUM>, image processing may be applied to the first image frame and/or second image frame based on a comparison between a first area of the first image frame corresponding to the region of interest and a second area of the second image frame corresponding to the region of interest. At step <NUM>, the first image frame and/or second image frame may be provided for display to a user.

<FIG> illustrates an exemplary system that may be used in accordance with techniques discussed in <FIG>, according to aspects of the present disclosure. <FIG> is a simplified functional block diagram of a computer that may be configured as server <NUM>, endoscope <NUM>, imaging device <NUM>, and/or user device <NUM>, according to exemplary embodiments of the present disclosure. Specifically, in one embodiment, any of the user devices, servers, etc., discussed herein may be an assembly of hardware <NUM> including, for example, a data communication interface <NUM> for packet data communication. The platform also may include a central processing unit ("CPU") <NUM>, in the form of one or more processors, for executing program instructions. The platform may include an internal communication bus <NUM>, and a storage unit <NUM> (such as ROM, HDD, SDD, etc.) that may store data on a computer readable medium <NUM>, although the system <NUM> may receive programming and data via network communications. The system <NUM> may also have a memory <NUM> (such as RAM) storing instructions <NUM> for executing techniques presented herein, although the instructions <NUM> may be stored temporarily or permanently within other modules of system <NUM> (e.g., processor <NUM> and/or computer readable medium <NUM>). The system <NUM> also may include input and output ports <NUM> and/or a display <NUM> to connect with input and output devices such as keyboards, mice, touchscreens, monitors, displays, etc. The various system functions may be implemented in a distributed fashion on a number of similar platforms, to distribute the processing load. Alternatively, the systems may be implemented by appropriate programming of one computer hardware platform.

The disclosed techniques may help enable efficient and effective procedures to breakup and/or remove material from a patient's organ. In particular, the user may easily view the processed frames to assist with, for example, removing kidney stones within the patient's kidney. The image may be clearer, with less visual obstructions, and the target kidney stone may be easier to track due to an indicator following its location. Therefore, in the kidney stone example, the user may more efficiently remove the kidney stones from specific locations within the patient's kidney.

Claim 1:
A system (<NUM>, <NUM>) for processing electronic images from a medical device (<NUM>), comprising:
a data storage device (<NUM>, <NUM>) storing instructions (<NUM>) for processing electronic images; and
a processor (<NUM>, <NUM>) configured to execute the instructions to perform a method for processing electronic images, the method including:
receiving (<NUM>) a first image frame and a second image frame from the medical device;
determining (<NUM>) a region of interest by subtracting the first image frame from the second image frame, the region of interest corresponding to a visual obstruction in the first image frame and/or second image frame;
applying (<NUM>) image processing to the first image frame and/or second image frame based on a comparison between a first area of the first image frame corresponding to the region of interest and a second area of the second image frame corresponding to the region of interest; and
providing (<NUM>) the first image frame and/or second image frame for display (<NUM>, <NUM>) to a user (<NUM>),
wherein the visual obstruction comprises a reflection, glare, piece of debris, and/or calculus, and
wherein the method executed by the system further comprises:
determining a border of a predetermined thickness around the region of interest; and
applying a color gradient across the border of the predetermined thickness around the region of interest.