Mitigating oversampling of registration data

Abstract

Systems and methods are disclosed for mitigating oversampling of data points collected by a medical device. In some aspects, a system is configured to receive, during an examination of an anatomical structure, data points of a sampled examination point cloud detected by a sensor of a medical device; determine, during the examination, at least one parameter associated with (i) the medical device and / or (ii) the received data points detected by the sensor, including a change in translational and / or rotational motion of the medical device, a distance from a data point to a nearest neighbor within the sampled examination point cloud, or a density of data points of a subset of the sampled examination point cloud corresponding to a sub-region of the anatomical structure; analyze the one or more parameters by comparing the one or more parameters to a threshold value; and record individual data points in a registered point cloud when the analyzed one or more parameters satisfy the respective threshold value.

Description

[0001] Cross-references to related applications

[0002] This patent document claims priority and benefit to U.S. Provisional Patent Application No. 63 / 001,169, filed March 27, 2020, entitled “MITIGATION OF REGISTRATION DATA OVERSAMPLING”. The entire contents of the aforementioned patent application are incorporated herein by reference as a part of the disclosure of this patent document. Technical Field

[0003] This disclosure relates to systems, apparatus, methods, and computer program products for registration instruments and image reference systems. Background Technology

[0004] Minimally invasive medical techniques aim to reduce the amount of tissue damaged during medical procedures, thereby reducing patient recovery time, discomfort, and harmful side effects. These techniques can be performed through natural openings in the patient's anatomy or through one or more surgical incisions. Through these natural openings or incisions, the operator can insert minimally invasive medical instruments to reach target tissue locations. Minimally invasive medical instruments include devices such as therapeutic, diagnostic, biopsy, and surgical instruments. Medical instruments can be inserted into anatomical channels and guided toward regions of interest within the patient's anatomy. Image-aided guidance can be used using the anatomical channel. Improved systems and methods are needed to accurately perform registration between images of the medical instruments and the anatomical channel. Summary of the Invention

[0005] Disclosed devices, systems, methods, and computer program products for mitigating oversampling of data points collected, for example, by a medical device prior to a medical procedure when guided to a specific area of ​​an anatomical structure to examine the airways in areas such as the lungs and bronchi.

[0006] In some embodiments, for example, a system for mitigating oversampling of data points includes: a medical device including sensors, wherein the medical device is insertable into an anatomical passage of a patient such that the sensors are operable to detect one or both of the position and movement of the medical device when inserted into the anatomical passage; and a computing device in communication with the medical device, the computing device including a processor and a memory coupled to the processor and storing instructions that, when executed by the processor, cause the system to perform operations including: receiving data points detected by the sensors of the medical device, the received data points being associated with one or both of the detected position and detected movement of the medical device; analyzing the received set of data points to determine motion parameters associated with movement or positional changes of the sensors of the medical device in a region of the anatomical passage, wherein the motion parameters include changes in one or both of translational and rotational motion of the sensors; comparing the motion parameters with a threshold to determine whether to accept the set of data points when the motion parameters meet the threshold or reject the set of data points when the motion parameters do not meet the threshold; and recording the accepted set of data points in a checkpoint cloud that can be used to register the medical device in an anatomical reference space.

[0007] In some embodiments, for example, a system for mitigating oversampling of data points includes: a medical device including sensors, wherein the medical device is insertable into an anatomical channel of a patient, such that the sensors are operable to detect one or both of the positioning and movement of a medical device when inserted into the anatomical channel; and a computing device in communication with the medical device, the computing device including a processor and a memory coupled to the processor and storing instructions that, when executed by the processor, cause the system to perform operations including: receiving data points detected by the sensors of the medical device, the received data points being associated with a detected positioning of the medical device; analyzing the received data points to determine a distance parameter associated with the data points and a distance between one or more nearest neighbors of the data points; comparing the distance parameter with a threshold to determine whether to accept data points among the received data points when the distance parameter meets the threshold, or to reject data points among the received data points when the distance parameter does not meet the threshold; and recording the accepted data points in a checkpoint cloud that can be used to register the medical device in an anatomical reference space.

[0008] In some embodiments, for example, a system for mitigating oversampling of data points includes: a medical device including sensors, wherein the medical device is insertable into an anatomical channel of a patient, such that the sensors are operable to detect one or both of the positioning and movement of a medical device when inserted into the anatomical channel; and a computing device in communication with the medical device, the computing device including a processor and a memory coupled to the processor and storing instructions that, when executed by the processor, cause the system to perform operations including: receiving data points detected by the sensors of the medical device, the received data points being associated with a detected positioning of the medical device; analyzing the received data points to determine a density parameter associated with the density of one or more data points of nearest neighbor data points; comparing the density parameter with a threshold to determine whether to accept one or more data points of the analyzed data points when the density parameter meets the threshold, or to reject multiple data points when the density parameter does not meet the threshold; and recording the accepted data points in a checkpoint cloud that can be used to register the medical device in an anatomical reference space.

[0009] In some embodiments, for example, a system for mitigating oversampling of data points includes: a medical device including a sensor, wherein the medical device is insertable into an anatomical passage of a patient, such that the sensor is operable to detect one or both of the positioning and movement of a medical device when inserted into the anatomical passage; and a computing device in communication with the medical device, the computing device including a processor and a memory coupled to the processor and storing instructions that, when executed by the processor, cause the system to perform operations including: receiving data points detected by the sensor of the medical device, the received data points being associated with the detection positioning of the medical device; analyzing the received data points to determine a density parameter associated with the density of one or more data points of nearest neighbor data points; comparing the density parameter with a threshold to determine whether to change the weighting of one or more data points within the analyzed data points; changing the weighting of one or more data points when the density parameter meets the threshold; and recording the data points to register the medical device in an anatomical reference space.

[0010] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory in nature and are intended to provide an understanding of the disclosure without limiting its scope. In this regard, additional aspects, features, and advantages of the disclosure will be apparent to those skilled in the art from the following detailed description. Attached Figure Description

[0011] Many aspects of this disclosure can be better understood with reference to the following accompanying drawings. The components in the drawings are not necessarily drawn to scale. Rather, the focus is on clearly illustrating the principles of this disclosure. The drawings should not be construed as limiting this disclosure to the specific embodiments depicted, but are for explanation and understanding only.

[0012] Figure 1 The diagram illustrates a method for mitigating oversampling of data points according to various embodiments of the present technology.

[0013] Figure 2 The description is based on Figure 1 The views are of various embodiments of the method for mitigating oversampled data, and are exemplary motion-based collection methods.

[0014] Figure 3 The description is based on Figure 1 The views are of various embodiments of the method for mitigating oversampled data and are exemplary point distance-based rejection methods.

[0015] Figure 4 The description is based on Figure 1 A view of various embodiments of the method for mitigating oversampled data based on an exemplary point density rejection method.

[0016] Figure 5 The description is based on Figure 1 A view of various embodiments of the method for mitigating oversampled data based on check density normalization.

[0017] Figure 6 Schematic diagrams are shown of robots or remote-controlled medical systems configured according to various embodiments of the present technology.

[0018] Figure 7 Schematic diagrams are shown of manipulator assemblies, medical device systems, and imaging systems configured according to various embodiments of the present technology.

[0019] Figure 8 This illustrates various embodiments of the technology extending within the patient's anatomical region. Figure 7 A schematic diagram of a part of a medical device system.

[0020] Figure 9 This view illustrates multiple coordinate points that form a representation on... Figure 8 Extending within the anatomical region shown Figure 8 A point cloud representing the shape of a part of a medical device system.

[0021] Figure 10 The view shown illustrates the view from... Figure 8 Extending within the anatomical region shown Figure 8 A guide image of the real patient's anatomy from a portion of the medical device system.

[0022] Figure 11 The view shown illustrates the view in Figure 8 A part of the medical device system extends within the anatomical area while Figure 8Intraoperative images of a portion of the anatomical region.

[0023] Figure 12 Schematic diagrams of display systems for displaying composite virtual guide images according to various embodiments of the present technology are shown, wherein Figure 7 and Figure 8 Medical device system registration Figure 8 The anatomical model of the anatomical region, the virtual guide image of the virtual patient's anatomical structure, and the real guide image of the real patient's anatomical structure within the anatomical region.

[0024] Specific implementation method

[0025] The systems and techniques disclosed herein can be used to register a medical device reference frame to an image reference frame for intraoperative anatomical images, including images of medical devices such as catheters. Typically, anatomical motion can cause intraoperative images to be too distorted to clearly isolate and delineate catheters, and can cause medical device positioning data to be disturbed. By representing the intraoperative image of the medical device as a point cloud (also known as an “image point cloud”) and the shape of the medical device (acquired by the sensor during image acquisition) as a point cloud (also known as a “sensor point cloud”), point-matching registration techniques such as Iterative Closest Point (ICP) can be used to register the sensor point cloud and the image point cloud. The robustness of this registration technique allows for the registration of an image reference frame to a medical device reference frame, despite patient anatomical motion causing data diffusion.

[0026] This document describes specific details relating to several embodiments of the present technology, some of which are referenced. Figures 1-12 While some of the embodiments are described in the context of guiding and performing medical procedures within a patient's lungs, other applications and other medical systems and devices embodiments, besides or alternative to those described herein, are within the scope of this technology. For example, unless otherwise stated or clearly stated from the context, the devices, systems, methods, and computer program products of this technology can be used in a variety of image-guided medical procedures, such as those performed on, in, or near a hollow patient anatomy, and more specifically, in procedures for examining, biopsiing, ablating, or otherwise treating tissue within and / or proximal to a hollow patient anatomy. Thus, for example, the systems, devices, methods, and computer program products of this disclosure can be used in one or more medical procedures associated with other patient anatomy, such as a patient's bladder, urinary tract, and / or heart.

[0027] It should be noted that other embodiments besides those disclosed herein are also within the scope of this technology. Furthermore, embodiments of this technology may have different configurations, components, and / or programs than those shown or described herein. Moreover, those skilled in the art will understand that embodiments of this technology may have configurations, components, and / or programs other than those shown or described herein, and these and other embodiments may be without several of the configurations, components, and / or programs shown or described herein without departing from this technology.

[0028] As used herein, the term "physician" should be understood to include any type of medical personnel who may be performing or assisting in medical procedures, and therefore includes doctors, nurses, medical technicians, other similar personnel, and any combination thereof. Additionally or alternatively, as used herein, the term "medical procedure" should be understood to include any manner and form of diagnosis, treatment, or both, including any preparatory activities associated with such diagnosis, treatment, or both. Thus, for example, the term "medical procedure" should be understood to include any manner and form of movement or positioning of medical devices in the anatomy room. As used herein, the term "patient" should be considered to include human and / or non-human (e.g., animal) patients to whom medical procedures are performed.

[0029] Example embodiments of techniques for mitigating oversampling of registration data

[0030] Point-matching registration techniques, such as ICP, are generally robust for registering collected data points in a point cloud because implementations of such techniques provide reliable registration data for establishing a reference frame to track the medical device relative to the patient's anatomical structure in which it is inserted. However, any point-matching technique, including ICP, is susceptible to some degree of error due to inaccuracies in the collected set of points. This is due to the inherent misalignment between the actual anatomical structure of the patient and the model of the anatomical structure. Typically, this error results from physical deformations (e.g., patient breathing, movement, displacement) relative to a previously acquired model of the patient's anatomy (e.g., an initial model created from previously acquired data, such as preoperative images of the patient's anatomy to generate the anatomical structure). This variability in physical deformation can lead to variability in the level of misalignment across different parts of the anatomical structure. Generally, optimal registration is considered to minimize the misalignment between the actual reference frame and the model-based reference frame.

[0031] Registration techniques such as ICP can mathematically compute the optimal alignment by minimizing the error between the collected set of points and the model-based set of points. However, because ICP is susceptible to inherent physiological misalignments, the resulting errors can be exacerbated by amplifying or assigning more weight to certain data points than others during the sampling process. Such sampling processes can be affected by how medical devices are manipulated to collect or sample point data from various regions. An example that worsens errors in point-matching registration is “overdriving” of insertable medical devices, where sensors associated with the insertable device are used to examine one or more regions of the patient’s anatomy disproportionately compared to other regions. Overdriving leads to oversampling and over-illumination of points in over-examined areas, resulting in inappropriate weighting of data points during point-matching registration.

[0032] As an example, some medical systems may implement registration protocols that require system users to locate sensors (e.g., associated with the system's insertable medical devices) in multiple anatomical regions. Registration protocols facilitate the collection of data points from a point cloud for registration with a global set of data (e.g., created from pre-procedure images), referred to as "examination data." For instance, a registration protocol might request or require the system user to move a medical device with associated sensor devices to a first region (e.g., determined from pre-procedure images), a second region, a third region, and so on, of the anatomical structure. However, during registration, the medical system may have little control over where, when, or how the system user "drives" the medical device with associated sensor devices. This makes registration prone to oversampling of data in regions of the anatomical structure where the user may "overdrive" the device more frequently than in other regions of interest. This can lead to inaccurate registration of the examination data with the global set of data.

[0033] One approach to this problem is to collect no examination data when the medical device is stationary, but only when the device moves relative to the anatomical structure. However, this technique has limitations because the data is still oversampled when the user repeatedly moves the device over a given area of ​​the anatomical structure. What is needed is an efficient and convenient (e.g., computationally inefficient) method to mitigate oversampling of examination data while the medical device performs registration.

[0034] In some embodiments of the present technology, a computer-implemented method for mitigating oversampling of data points collected by sensors associated with a medical device includes: analyzing (i) one or more parameters of the sensors (of the medical device) and (ii) one or more parameters of the sampled data points, and comparing one or both of the analyzed sensor parameters and / or data point parameters with thresholds in real time, wherein when one or more corresponding parameters meet the thresholds, individual data points from the sampled data points are recorded in a registration point cloud. Figure 1Example embodiments of such methods are described.

[0035] Figure 1 For example, there is a flowchart illustrating a method 1000 for mitigating oversampling of data points according to various embodiments of the present technology. Various embodiments of method 1000 may mitigate oversampling based on point sampling techniques and / or based on density normalization techniques. All or a subset of the steps of method 1000 may be implemented by a computing device, such as a control system of a medical system or device, including various components or devices of a robot or remote operating system. Method 1000 includes a set of operations or processes 1010-1040.

[0036] A computing device for implementing 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 according to processes 1010-1040. In some implementations where the computing device is included in a robotic or remotely operated medical system, the computing device communicates data with a medical device system including medical devices and sensors and receives sensor data for mitigating oversampling of data points. The sensors are configured to generate positioning sensor data and / or motion sensor data during a registration protocol when the medical device is driven within one or more anatomical structures of a patient (e.g., driven through one or more anatomical passages of the patient). In this manner, the positioning sensor data is associated with one or more locations of the medical device within the anatomical passage, and the motion sensor data is associated with translational and / or rotational movements of the medical device within the anatomical passage. Optionally, in some embodiments, the medical device system includes an image capture device configured to capture image data of the patient's anatomical structure within the anatomical passage during data sampling of one or more anatomical structures. References will be made later. Figure 6 and Figure 7 The exemplary robot or remotely operated medical system 100 (“medical system 100”) discussed herein describes method 1000.

[0037] In process 1010, method 1000 receives data from sensors (e.g., sensors) on a computing device during data sampling of one or more anatomical structures of the patient by sensors. Figure 6 and Figure 7 The data points corresponding to the sampling checkpoint cloud detected by the shape sensor 233 and / or positioning measurement device 239 of the medical device system 204 shown. The data points received at the computing device can be associated with the positioning and / or motion of the sensor, for example, and thus with the positioning and / or motion of the medical device.

[0038] In process 1020, method 1000 determines, at a computing device, a first parameter associated with a medical device (e.g., sensors and / or other components of the medical device) and / or a second parameter associated with the received data points. In some implementations of process 1020, the first parameter includes motion parameters associated with the medical device. In such implementations, determining the first parameter may include determining changes in translational and / or rotational motion of the medical device, such as changes in roll or pitch and / or deflection values ​​of sensors of the medical device (e.g., medical device system 204 at the tip of shape sensor 233). In some implementations of process 1020, the second parameter may include point distance parameters and / or point density parameters associated with the received data points. In such implementations, determining the second parameter may include determining (i) the distance from a data point to its nearest neighbor within a sampled checkpoint cloud, and / or (ii) the density of data points, for example, within a predefined subset of the sampled checkpoint cloud corresponding to a subregion of an anatomical structure. One, some, or all of the above example features may be implemented by process 1020.

[0039] In process 1030, method 1000 analyzes the first parameter and / or the second parameter at a computing device by comparing a first parameter with a first threshold and / or by comparing a second parameter with a second threshold. For example, the first threshold and the second threshold may each include a threshold value or a range of values. As an example, the first threshold value or range of values ​​may include the rate (or range of rates) exhibited by the sensor through movement from a previous sample. As another example, the second threshold value or range of values ​​may include the minimum distance or range of distances by which the sensor translates or rotates from a previous sample (e.g., a previously acquired sample). In some implementations of process 1030, the second parameter includes a determined distance from a data point to its nearest neighbor within the sampling checkpoint cloud, which can be compared to a distance threshold. In some implementations of process 1030, the second parameter includes a determined density value of a data point, which can be compared to a density threshold. One, some, or all of the above example features may be implemented by process 1030.

[0040] In process 1040, when the first parameter and / or the second parameter meets a corresponding threshold, method 1000 records individual data points (among the received data points) in the registration point cloud at a computing device. In this way, for example, one or more identified individual data points from the received data points can be added to the recorded coordinate points, which form a localization point cloud data representing the shape of a medical device within an anatomical region. In some implementations of process 1040, the received data points are initially recorded in the registration point cloud, and then process 1040 rejects any individual data points when the determined second parameter meets a threshold value. However, in some implementations of process 1040, process 1040 includes adding individual data points only when the determined second parameter meets a threshold value. However, in some implementations, before recording individual data points, process 1040 can be implemented to reduce the weighting of data points when the determined data point density (as the second parameter) exceeds a threshold density.

[0041] In some embodiments, method 1000 provides techniques for mitigating oversampled data based on motion collection. However, in some embodiments, method 1000 provides techniques for mitigating oversampled data based on point distance rejection. However, in some embodiments, method 1000 provides techniques for mitigating oversampled data based on point density rejection.

[0042] Figure 2 This is a flowchart illustrating an example of an oversampling mitigation method 2000 based on motion collection according to some embodiments of method 1000. For example, method 2000 can be used to limit the collection of examination data until motor encoder values ​​from either IO or pitch / yaw have changed sufficiently to be considered as motion of a medical device such as a catheter. All or a subset of the steps of method 2000 can be implemented by a computing device (e.g., the control system 112 of medical system 100 described later, or various other components or devices of a robot or remote operating system). In various implementations of method 2000, for example, sensors may include shape sensor 233 and / or positioning measurement device 239 of medical device system 204, and method 2000 may be implemented during examination of one or more anatomical structures of a patient, such as during the implementation of sensor system 208 in a registration protocol.

[0043] In process 2010, method 2000 receives examination data points detected by sensors (e.g., shape sensor 233) of the medical device to determine when the medical device moves with one or more specific translational and / or rotational movements, such as rolling motion (Δθ) or pitch or yaw motion. During the inspection performed by the sensors (process 2010), method 2000 includes process 2020 to determine changes in translational and / or rotational motion (e.g., ΔIO or pitch / yaw values). In process 2030, the method compares the changes with a threshold (e.g., a threshold value or range of values) associated with the translational and / or rotational motion. In process 2040, method 2000 records examination data points in the point cloud when the determined motion change meets the threshold, and does not record (e.g., discards) examination data points in the point cloud when the determined motion change does not meet the threshold. In this way, for example, method 2000 can consider the collection limitations of the examination data that would be included in the point cloud based on sensor (e.g., encoder) values ​​of a specific magnitude (such as IO or obvious changes in pitch / yaw) as the movement of the medical device within the anatomical region during registration—rather than simply the movement of the medical device.

[0044] In an example implementation of method 2000, the shape sensor 233 and / or positioning measuring device 239 of the medical device system 204 are driven in one or more anatomical passages of the patient. In process 2010, the control system 112 of the medical system 100 receives all data generated by the shape sensor 233 and / or positioning measuring device 239. In process 2020, the control system 112 determines whether there is a movement and / or positioning change of the shape sensor 233 and / or positioning measuring device 239; if a determined change exists, the control system 112 determines the value of the change, i.e., the increment of movement and / or the increment of position. If no change is determined, the control system 112 assigns zero increment to the movement and / or positioning parameters (e.g., a first parameter). In process 2030, the control system 112 compares the determined change value with a threshold value (or a range of threshold values) to determine whether to accept or reject the received examination data sampled from the medical device system 204. In a non-limiting example, the threshold value is a positioning change of 0.5 mm from a previous collection point. A threshold value (or threshold range) can be predetermined and stored in the memory of the control system 112. In process 2040, when it is determined in process 2030 that the determined change value meets the threshold value, the control system 112 records examination data points in the point cloud. For example, when the increment is zero or less than the threshold (or outside any threshold range), the examination data will be rejected in process 2040. For example, when the increment is at or greater than the threshold (or within the threshold range), the examination data will be accepted in process 2040. In this way, method 2000 mitigates potential oversampling by registering the medical device system 204 in anatomical space (e.g., which corresponds to the image space from the preoperative images) using only the accepted data through system 100.

[0045] Figure 3 This is a flowchart illustrating an example of an oversampling mitigation method 3000 based on point distance rejection according to some embodiments of method 1000. All or a subset of the steps of method 3000 may be implemented by a computing device, such as the control system 112 of medical system 100, or various other components or devices of a robot or remote operating system. In various implementations of method 3000, for example, sensors may include shape sensors 233 and / or positioning measurement devices 239 of medical device system 204, and method 3000 may be implemented, for example, during the implementation of sensor system 208, during examination of one or more anatomical structures of a patient in a registration protocol.

[0046] In process 3010, method 3000 receives examination data points detected by sensors of the medical device (e.g., shape sensor 233 at the tip and / or body), which are recorded into a sampled examination point cloud. In process 3020, method 3000 determines, for example, in real time during sensor inspection (e.g., in process 3010), the distance from the data point to its nearest neighbor within the sampled examination point cloud. In process 3030, method 3000 compares the determined distance with a threshold distance (e.g., a threshold distance value or a range of distance values). In process 3040, when the determined distance of a data point is within the threshold distance of the nearest neighbor, method 3000 rejects the data point from the recorded sampled examination point cloud. In this way, for example, method 3000 adds the examined data points to the point cloud in a real-time evaluation manner during the registration protocol of the medical device and rejects those data points whose distances are determined to be too close to the nearest neighbor.

[0047] In an example implementation of method 3000, the shape sensor 233 and / or positioning measurement device 239 of the medical device system 204 are driven in one or more anatomical passages of the patient. In process 3010, the control system 112 of the medical system 100 receives all data generated by the shape sensor 233 and / or positioning measurement device 239 and initially records all data into a point cloud. In process 3020, the control system 112 examines at least one set of recorded data entering the point cloud by determining the distances of one or more data points within that set to other nearest neighbor data points within that set. In process 3030, the determined distance between each data point and its nearest neighbor is compared to a threshold (e.g., a threshold value or a threshold range), which, for example, provides the control system 112 with the “proximity” of the data point to its nearest neighbor. For example, in implementations of processes 3020 and 3030, the control system 112 may calculate a set of K nearest neighbor distances and evaluate the point using any number of nearest neighbors. In one case, the number K of nearest neighbors may be specified by the user or software. Alternatively, the number of nearest neighbors can be determined as a group of all points located within a specified distance from the point in question. In process 3040, data points identified from the point cloud as "too close" to their nearest neighbors (i.e., those whose distance is within a threshold distance of one or more of their nearest neighbors) are rejected.

[0048] Figure 4This is a flowchart illustrating an example of an oversampling mitigation method 4000 based on point density rejection according to some embodiments of method 1000. All or a subset of the steps of method 4000 may be implemented by a computing device, such as the control system 112 of medical system 100, or various other components or devices of a robot or remote operating system. In various implementations of method 4000, for example, sensors may include shape sensors 233 and / or positioning measurement devices 239 of medical device system 204, and method 4000 may be implemented, for example, during the examination of one or more anatomical structures of a patient in a registration protocol during the implementation of sensor system 208.

[0049] In process 4010, method 4000 receives examination data points detected by sensors of the medical device (e.g., shape sensor 233 at the tip and / or body), which are recorded into a sampled examination point cloud. In process 4020, for example, within a subset of the sampled examination point cloud corresponding to a sub-region of an anatomical structure (e.g., a predefined subset), method 4000 determines the density of the data points in real time, for example, during sensor examination (e.g., in process 4010). In process 4030, method 4000 compares the determined density with a threshold density (e.g., a threshold density value or a density value range). In process 4040, when the density of the determined data point (including the data point) is within the threshold density of the sub-region, method 4000 rejects the data point from the recorded sampled examination point cloud. In this way, for example, method 4000 adds the examined data point to the point cloud and rejects the data point in real time when evaluating against a point density threshold (e.g., which may be a point density threshold within one or more regions of an anatomical structure of various sizes, e.g., predefined).

[0050] In an example implementation of method 4000, the shape sensor 233 and / or positioning measurement device 239 of the medical device system 204 are driven in one or more anatomical passages of the patient. In process 4010, the control system 112 of the medical system 100 receives all data generated by the shape sensor 233 and / or positioning measurement device 239 and initially records all data into a point cloud. In process 4020, the control system 112 begins to examine the density of data points within a set of recorded data entering the point cloud. For example, in process 4020, the control system 112 determines the density of data points within the set, which includes an analysis of the data points within the set relative to their nearest neighbor data points. In process 4030, the determined density of the data points within the set is compared to a threshold (e.g., a threshold value or threshold range), which, for example, provides the control system 112 with the “density” of data points relative to their nearest neighbors within the set. For example, in implementations of processes 4020 and 4030, the control system 112 may calculate a set of K nearest neighbor distances and use any number of nearest neighbors to evaluate each point. When a group is determined to be "too dense" within a data point group, the control system 112 can reject one or more data points to mitigate oversampling. In process 4040, data points determined to be in a "dense group" relative to their nearest neighbors are rejected from the point cloud.

[0051] Figure 5 This is a flowchart illustrating an example of an oversampling mitigation method 5000 based on examination density normalization according to some embodiments of method 1000. Similar to the methods described above, all or a subset of the steps of method 5000 can be implemented using computing devices such as the control system 112 of medical system 100, or various other components or devices of a robot or remote operating system. In various implementations of method 5000, sensors may include shape sensors 233 and / or positioning measurement devices 239 of medical device system 204, and method 5000 may be implemented, for example, during the implementation of sensor system 208 during examination of one or more anatomical structures of a patient in a registration protocol.

[0052] In some examples of Method 5000, the examination data points are collected by a sensor, but some data points may be removed if oversampling occurs in a given region. A straightforward approach, for example, is to retain all points but reduce the weight of each point within a densely examined region. This can be implemented as an enhancement to the ICP algorithm, since the weighting is a variable used by the standard ICP algorithm. Within the example ICP algorithm, at each step, registration is computed using the cumulative set of nearest-neighbor matches between the examined point cloud and a comparative data set of anatomical structures (e.g., a preoperative image data set of airway trees). In the implementation of Method 5000, for example, by reducing the weights applied to point matches within a given region, the method can effectively reduce or correct for oversampling in that region. Method 5000 includes a set of operations or procedures 5010-5040 described below.

[0053] In process 5010, method 5000 receives examination data points detected by sensors (e.g., shape sensor 233) of the medical device, which may be recorded into a sampled examination point cloud based on the results of processes 5020 and 5030. In process 5020, for example, in a subset of the sampled examination point cloud corresponding to a sub-region of the anatomical structure (e.g., a predefined subset), method 5000 determines the density of the data points in real time, for example, during the sensor examination (e.g., in process 5010). For example, in some implementations of process 5010, the determined density is based on a distance parameter from the location of the medical device within the anatomical region. In process 5030, method 5040 compares the determined density with a threshold density (e.g., a threshold density value or a range of density values) for the sub-region.

[0054] Method 5000 includes procedure 5040 to (i) record the collected checkpoint data points into a checkpoint cloud and (ii) reduce the weights associated with data points within a sub-region (e.g., referred to as an oversampled sub-region) when the determined density exceeds a density threshold. In some implementations of procedure 5040, for example, the weights are normalized for the weights associated with data points in the oversampled sub-region, wherein the normalization process includes dividing the weights by the total number of matches with the nearest checkpoints. As an illustrative example, procedure 5040 can be implemented where the weights are normalized such that the points in an anatomical structure (e.g., the lung airway tree) closest to multiple checkpoints will have their weights divided by the total number of matches. In some examples, the matches can be down-weighted or up-weighted based on the local density of the points. In such cases, for example, the density can be calculated based on the number of checkpoints in a given volume.

[0055] However, in some implementations of process 5040, the weighting is normalized by smoothing data points along a length line that traverses at least a portion of the oversampled sub-region. As an illustrative example, process 5040 can be implemented where the density is normalized by calculating the number of matches occurring along a given length of an anatomical structure (e.g., airways in a lung airway tree). In such cases, for example, larger oversampled regions can be smoothed by normalizing the local weighted density of all checkpoints along each airway. The result would be registration that is balanced over the total length of the driving airway.

[0056] Embodiments of a robot or remotely operated medical system for implementing the disclosed method

[0057] Figure 6 This is a schematic diagram of a robotic or remotely operated medical system 100 (“Medical System 100”) configured according to various embodiments of the present technology. As shown, Medical System 100 includes a manipulator assembly 102, a medical device system 104, a main assembly 106, and a control system 112. The manipulator assembly 102 supports the medical device system 104 and drives the medical device system 104 in the direction of the main 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 setting 101. In this respect, the main assembly 106 typically includes one or more control devices operated by an operator 105 (e.g., 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 implementing control between the medical device system 104, the main assembly 106, and / or other components of Medical System 100. The control system 112 may also include programmable instructions (e.g., a non-transitory computer-readable medium storing instructions) to implement any or more of the methods described herein, including instructions for providing information to the display system 110 and / or instructions for processing data for registering medical device 104 with a patient by the medical system 100 for various medical procedures (as described in more detail below). The manipulator component 102 may be a remotely operated, non-remotely operated, or a hybrid of both. Therefore, all or part of the main component 106 and / or all or part of the control system 112 may be located inside or outside the surgical environment 101.

[0058] In some embodiments, to assist operator 105 in controlling manipulator assembly 102 and medical device system 104, medical system 100 further includes sensor system 108, endoscopic imaging system 109, imaging system 118, virtual visualization system 115, and / or display system 110. In some embodiments, sensor system 108 includes a position / positioning sensor system (e.g., an electromagnetic (EM) sensor system) and / or shape sensor system for determining the location, orientation, velocity, rate, posture, and / or shape of medical device system 104 (e.g., when medical device system 104 is inside patient 103). In these and other embodiments, endoscopic imaging system 109 includes one or more image capture devices (not shown) (such as imaging endoscope assemblies and / or imaging instruments) that record endoscopic image data, including concurrent or real-time images of patient anatomy (e.g., video, still images, etc.). Images captured by endoscopic imaging system 109 may be, for example, two-dimensional or three-dimensional images of patient anatomy captured by imaging instruments positioned within patient 103, and are referred to below as “realistic guided images.”

[0059] In some embodiments, the medical device system 104 may include components of the sensor system 108 and / or the endoscopic imaging system 109. For example, components of the sensor system 108 and / or the endoscopic imaging system 109 may be integrally or removably coupled to the medical device system 104. Alternatively, the endoscopic imaging system 109 may include a separate endoscope (not shown) attached to a separate manipulator assembly (not shown) that can be used with the medical device 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 interacts with or otherwise executes with one or more computer processors (such as one or more computer processors 114) of the control system 112.

[0060] The imaging system 118 of the medical system 100 can be positioned 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 medical procedures. In some embodiments, the imaging system 118 includes a moving C-arm cone-beam computed tomography (CT) imaging system for generating three-dimensional images. For example, the imaging system 118 may include a DynaCT imaging system from Siemens Corporation or other suitable imaging systems. In these and other embodiments, the imaging system 118 may include other imaging techniques, including magnetic resonance imaging (MRI), fluoroscopy, thermal imaging, ultrasound, optical coherence tomography (OCT), thermal imaging, impedance imaging, laser imaging, nanotube X-ray imaging, etc.

[0061] In these and other embodiments, the control system 112 also includes a virtual visualization system 115 to provide guidance assistance to the operator 105 when controlling the medical device system 104 during image-guided medical procedures. For example, virtual guidance using the virtual visualization system 115 may be based on a set of preoperative or intraoperative data acquired regarding the anatomical pathways of the patient 103 (e.g., based on a reference to data generated by the sensor system 108, the endoscopic imaging system 109, and / or the imaging system 109). In some implementations, for example, the virtual visualization system 115 processes image data of the patient's anatomical structures captured using the imaging system 118 (e.g., to generate an anatomical model of the anatomical regions of the patient 103). The virtual visualization system 115 can register image data and / or anatomical models to data generated by the sensor system 108 and / or to data generated by the endoscopic imaging system 109 to (i) determine the location, posture, orientation, shape and / or movement of the medical device system 104 within the anatomical model (e.g., to generate composite virtual guide images), and / or (ii) determine virtual images (not shown) of the patient's anatomical structures from the perspective of the medical device system 104 within the patient 103. For example, the virtual visualization system 115 can register the anatomical model to positioning sensor data generated by the positioning sensor system 108 and / or to endoscopic image data generated by the endoscopic imaging system 109, in order to (i) map the tracked positioning, orientation, posture, shape and / or movement of the medical device system 104 in the anatomical region to the correct positioning within the anatomical model, and / or (ii) determine a virtual guide image of the virtual patient anatomy of the anatomical region from the perspective of the medical device system 104 at the position within the anatomical model corresponding to the position of the medical device system 104 within the patient 103.

[0062] Display system 110 can display various images or illustrations of patient anatomy and / or medical device system 104 generated by sensor system 108, endoscopic imaging system 109, imaging system 118, and / or virtual visualization system 115. In some embodiments, display system 110 and / or main component 106 can be oriented such that operator 105 can remotely present sensor control manipulator component 102, medical device system 104, main component 106, and / or control system 112.

[0063] As described above, the manipulator assembly 102 drives the medical device system 104 in the direction of the main assembly 106 and / or the control system 112. In this respect, the manipulator assembly 102 may include selectable degrees of freedom of motion, which may be motorized and / or remotely operated, and selectable degrees of freedom of motion, which may be non-motorized and / or non-remotely operated. For example, the manipulator assembly 102 may include multiple actuators or motors (not shown) that drive inputs to the medical device system 104 in response to commands from the control system 112. The actuators may include a drive system (not shown) that, when coupled to the medical device system 104, can advance the medical device system 104 into an anatomical opening created naturally or surgically. Other drive systems may move a distal portion (not shown) of the medical device system 104 with multiple degrees of freedom, which may include three linear degrees of freedom (e.g., linear motion along an X, Y, Z Cartesian coordinate system) and three rotational degrees of freedom (e.g., rotation about an X, Y, Z Cartesian coordinate system). In addition, the actuator can be used to actuate the articulated end effector of the medical device system 104 (e.g., for holding tissue in the jaws of a biopsy device).

[0064] Figure 7 This is a schematic diagram of a manipulator assembly 202, a medical device system 204, and an imaging system 218 configured in a surgical setting 201 and according to various embodiments of the present technology. In some embodiments, the manipulator assembly 202, the medical device system 204, and / or the imaging system 218 are respectively Figure 6 The manipulator assembly 102, medical device system 104, and / or imaging system 118. As shown in the figure. Figure 7 The surgical environment 201 described herein has a surgical reference frame (X). S Y S Z S Patient 203 was located on platform 207, and Figure 7 The medical device system 204 described herein has a medical device reference frame (X) within the surgical environment 201. M Y M Z M During medical procedures, patient 203 may remain still within surgical environment 201 because the patient's overall movement can be restricted by sedation, restraint, and / or other means. In these and other embodiments, circulatory anatomical movement of patient 203 (including respiratory and cardiac movement) may continue unless patient 203 is instructed to hold his or her breath to temporarily suspend respiratory movement.

[0065] Manipulator assembly 202 includes an instrument holder 226 mounted to insertion stage 228. In some embodiments, insertion stage 228 is fixed within surgical environment 201. Alternatively, insertion stage 228 may be movable within surgical environment 201 but has a known position within surgical environment 201 (e.g., via tracking sensors or other tracking devices). In these alternatives, a medical device reference frame (X) is used. M Y M Z M ) relative to the surgical reference frame (X S Y S Z S It is fixed or otherwise positioned relative to a surgical reference system. 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 segments.

[0066] Figure 7 The medical device system 204 includes an elongated device 231, a medical device 232, a device body 235, a sensor system 208, and an endoscopic imaging system 209. In some embodiments, the elongated device 231 is a flexible catheter defining a channel or lumen 244. The size and shape of the channel 244 may be designed to receive the medical device 232 (e.g., via the proximal end 236 of the elongated device 231 and / or the device port (not shown)) and facilitate delivery of the medical device 232 to the distal portion 238 of the elongated device 231. As shown, the elongated device 231 is coupled to the device body 235, which is in turn coupled and secured relative to the device holder 226 of the manipulator assembly 202.

[0067] In operation, for example, the manipulator assembly 202 can control the movement of the elongated device 231 inserted into the patient 203 via a natural or surgically created anatomical opening (e.g., proximal and / or distal movement along axis A) to facilitate guiding the elongated device 231 through the anatomical passage of the patient 203 and / or to facilitate delivery of the distal portion 238 of the elongated device 231 to a target location within the patient 203. For example, the instrument holder 226 and / or insertion stage 228 may include actuators (not shown), such as servo motors, which facilitate control of the movement of the instrument holder 226 along the insertion stage 228. Additionally or alternatively, in some embodiments, the manipulator assembly 202 can control the movement of the distal portion 238 of the elongated device 231 in multiple directions, including deflection, pitch, and roll rotation (e.g., to guide patient anatomy). For this purpose, the elongated device 231 may accommodate or include cables, linkages, and / or other steering controls (not shown) that can be used by the manipulator assembly 202 to controllably bend the distal portion 238 of the elongated device 231. For example, the elongated device 231 may accommodate at least four cables that can be used by the manipulator assembly 202 to provide (i) independent "up and down" steering to control the pitch of the distal portion 238 of the elongated device 231 and (ii) independent "left and right" steering of the elongated device 231 to control the deflection of the distal portion 238 of the elongated device 231.

[0068] Medical device 232 of medical device system 204 can be used for medical procedures such as examination of anatomical access, surgery, biopsy, ablation, illumination, irrigation, and / or aspiration. Therefore, medical device 232 may include image-capturing probes, biopsy instruments, laser ablation fibers, and / or other surgical, diagnostic, and / or therapeutic tools. For example, medical device 232 may include an endoscope having one or more image-capturing devices 247 positioned at a distal portion 237 of medical device 232 and / or at other locations along medical device 232. In these embodiments, when medical device 232 is within the anatomical region of patient 203, image-capturing devices 247 may capture one or more real images or videos (e.g., a sequence of one or more real guide image frames) of the anatomical access and / or other patient anatomy.

[0069] As described above, the medical device 232 can be deployed to and / or delivered to a target location within the patient 203 via the passage 244 defined by the elongated device 231. In embodiments where the medical device 232 includes an endoscope or other medical devices having an image capturing device 247 at the distal portion 237 of the medical device 232, the image capturing device 247 can be advanced to the distal portion 238 of the elongated device 231 before, during, and / or after the manipulator assembly 202 guides the distal portion 238 of the elongated device 231 to the target location within the patient 203. In these embodiments, the medical device 232 can be used as an examination instrument to capture real images and / or videos of anatomical passages and / or other patient anatomy, and / or to assist an operator (e.g., a physician) in guiding the distal portion 238 of the elongated device 231 through the anatomical passage to the target location.

[0070] As another example, after the manipulator assembly 202 positions the distal portion 238 of the elongated device 231 close to a target location within the patient 203, the medical device 232 can advance beyond the distal portion 238 of the elongated device 231 to perform a medical procedure at the target location. Continuing with the example above, after all or part of the medical procedure at the target location has been completed, the medical device 232 can retract into the elongated device 231 and, additionally or alternatively, be removed from the proximal end 236 of the elongated device 231 or from another instrument port (not shown) along the elongated device 231.

[0071] exist Figure 7 In the exemplary embodiment shown, the sensor system 208 of the medical device system 204 includes a shape sensor 233 and a positioning measurement device 239. In some embodiments, the sensor system 208 includes... Figure 6 The sensor system 208 may include all or part of it. In these and other embodiments, the shape sensor 233 of the sensor system 208 includes an optical fiber extending within and aligned with an elongated 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.

[0072] The shape sensor 233 forms an optical fiber bending sensor for determining the shape of the elongated device 231. In some embodiments, the optical fiber having a fiber Bragg grating (FBG) can be used to provide strain measurements in one-dimensional or multi-dimensional structures. Various systems and methods for monitoring the shape and relative positioning of optical fibers in three dimensions are described in more detail in the following patents: U.S. Patent Application Publication No. 2006-0013523 (filed July 13, 2005) (disclosing an optical fiber positioning and shape sensing device and related methods thereof); U.S. Patent No. 7,781,724 (filed September 26, 2006) (disclosing an optical fiber positioning and shape sensing device and related methods thereof); U.S. Patent No. 7,772,541 (filed March 12, 2008) (disclosing Rayleigh scattering-based optical fiber positioning and / or shape sensing); and U.S. Patent No. 6,389,187 (filed June 17, 1998) (disclosing an optical fiber bending sensor), which are incorporated herein by reference in their entirety. In these and other embodiments, the sensor of this technology may employ other suitable strain sensing techniques, such as Rayleigh scattering, Raman scattering, Brillouin scattering, and fluorescence scattering. In these and other embodiments, other techniques may be used to determine the shape of the elongated device 231. For example, the history of the orientation of the distal portion 238 of the elongated device 231 may be used to reconstruct the shape of the elongated device 230 over time intervals.

[0073] In some embodiments, the shape sensor 233 is fixed at a proximal point 234 on the device body 235 of the medical device system 204. In operation, for example, the shape sensor 233 measures from the proximal point 234 to another point along the optical fiber (such as the distal portion 238 of the elongated device 231) in a medical device reference frame (X). M Y M Z M The shape of the shape sensor 233. The proximal point 234 of the shape sensor 233 can move together with the instrument body 235, but the position of the proximal point 234 can be known (e.g., via a tracking sensor or other tracking device).

[0074] The positioning measuring device 239 of the sensor system 208 provides information about the positioning 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 positioning measuring device 239 includes a resolver, encoder, potentiometer, and / or other sensors that determine the rotation and / or orientation of an actuator (not shown) that controls the movement of the instrument holder 226 of the manipulator assembly 202 and thus controls the movement of the instrument body 235 of the medical device system 204.

[0075] Figure 8It extends within the anatomical region 350 (e.g., human lung) of patient 203 according to various embodiments of the present technology. Figure 7 A schematic diagram of a portion of the medical device system 204. Specifically, Figure 8 This describes an elongated device 231 of a medical device system 204 extending within a branch anatomical passage 352 of the anatomical region 350. The anatomical passage 352 includes a trachea 354 and a bronchus 356.

[0076] like Figure 8 As shown, the elongated device 231 has a position, orientation, posture, and shape within the anatomical region 350, all or part of which (except for or in lieu of movement, such as speed or rate) can be captured by the shape sensor 233 and / or positioning measurement device 239 of the sensor system 208 to examine the anatomical passage 352 of the anatomical region 350. Specifically, through the medical device reference frame (X... M Y M Z M The positioning information of the medical device system 204 within the anatomical region 350 is aggregated in the sensor system 208, and the shape sensor 233 and / or positioning measurement device 239 can examine the anatomical passage 352. The positioning information can be recorded as a set of two-dimensional or three-dimensional coordinate points. In an example where the anatomical region 350 is a human lung, the coordinate points can represent the position of the distal portion 238 of the elongated device 231 and / or other portions of the elongated device 231 as it advances through the trachea 354 and bronchi 356. In these and other embodiments, the set of coordinate points can represent one or more shapes of the elongated device 231 as it advances through the anatomical region 350. In these and other embodiments, the coordinate points can represent positioning data of other parts of the medical device system 104 (e.g., medical device 232).

[0077] Coordinate points can be combined to form a point cloud data. For example, Figure 9 This describes the formation of a plurality of coordinate points 462 in positioning point cloud data 460 according to various embodiments of the present technology. This positioning point cloud data 460 represents the position of the elongated device 231 in the anatomical region 350 (previously in…). Figure 8 The shape of the elongated device 231 within the sensor system 208 is shown in the diagram. Specifically, during the data acquisition cycle of the sensor system 208, the shape sensor 233 (previously located in...) is used... Figure 7 and Figure 8 (as shown in) and / or positioning measuring device 239 (previously in) Figure 7 The location point cloud data 460 is generated from a set of all or a subset of the recorded coordinate points 462 (shown in the diagram). The location point cloud data 460 can be generated by implementing the disclosed example embodiment of method 1000.

[0078] In some embodiments, a point cloud (e.g., point cloud 460) may include a collection of all or a subset of coordinate points recorded by sensor system 208 during image capture periods spanning multiple shapes, positions, orientations, and / or poses of the elongated device 231 within anatomical region 350. In these embodiments, the point cloud may include coordinate points captured by sensor system 208 representing multiple shapes of the elongated device 231 as it advances or moves through the patient's anatomy during image capture. Additionally or alternatively, because the configuration (including shape and position) of the elongated device 231 within patient 203 may change due to anatomical movement during image capture periods, in some embodiments the point cloud may include multiple coordinate points 462 captured by sensor system 208 as the elongated device 231 passively moves within patient 203, representing the shape of the elongated device 231. The point cloud of coordinate points captured by sensor system 208 may be registered to different models or sets of data of the patient's anatomy. For example, the localization point cloud data 460 may be used for registration with different models of branch anatomical pathways 352.

[0079] Refer again Figure 7 The endoscopic imaging system 209 of the medical device system 204 includes one or more image capturing devices configured to simultaneously capture anatomical passages within the patient 203 in the elongated device 231 and / or the medical device 232 (e.g., Figure 8 The endoscopic imaging system 209 may include one or more images and / or videos (e.g., image frame sequences) of the anatomical passage 352 and / or other patient anatomical structures. For example, the endoscopic imaging system 209 may include (i) an image capturing device 247 positioned at the distal portion 237 of the medical device 232 and / or (ii) one or more other image capturing devices (not shown) positioned at other locations along the medical device 232. In these and other embodiments, the endoscopic imaging system 209 may include one or more image capturing devices (not shown) positioned at the distal portion 238 and / or at other locations along the elongated device 231. In some embodiments, the endoscopic imaging system 209 may include Figure 6 All or part of the endoscopic imaging system 109.

[0080] like Figure 8 As shown, the image capturing device 247 of the medical device 234 is positioned at the distal portion 238 of the elongated device 231. In this embodiment, the image capturing device 247 examines the anatomical passage 352 by simultaneously capturing a true image of the anatomical passage 352 as the elongated device 231 is advanced through the trachea 354 and bronchus 356 of the anatomical region 350.

[0081] Figure 10 The anatomical region 350, such as that captured by the image capture device 247 of the medical device system 204, is... Figure 8 An example of an endoscopic video image frame 570 (e.g., a real image, such as a still image, a video image frame, etc.) of the patient's anatomical structure of the anatomical passage 352. As shown, the real image 570 illustrates the two bronchi 356 (in the anatomical passage 352) from the perspective of the medical device 232. Figure 8 The branch point 571 (within the anatomical region 350 described herein). In this example, the viewing angle is from the distal tip of the medical device 232, making the medical device 232 invisible in the true image 570. In other embodiments, the image capturing device 247 may be positioned at another location along the medical device 232 and / or along the elongated device 231, such that the true image 570 is acquired from another viewpoint of the medical device 232 and / or from another viewpoint of the elongated device 231. Depending on the positioning of the medical device 232 and the elongated device 231 relative to each other, a portion of the medical device 232 and / or the elongated device 231 may be visible within the true image 570.

[0082] Refer again Figure 7 The real images captured by the endoscopic imaging system 209 can help guide the distal portion 238 of the elongated device 231 through the anatomical passage of the patient 203 (e.g., Figure 8 The anatomical access channel 352) and / or delivery of the distal portion 238 of the elongated 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 may help (i) guide the distal portion of the medical device 232 beyond the distal portion 238 of the elongated device 231, (ii) deliver the distal portion of the medical device 232 to a target location within the patient 203, and / or (iii) visualize the patient's anatomy during medical procedures. In some embodiments, each real image captured by the endoscopic imaging system 209 may be associated with a timestamp and / or location within the anatomical region of the patient 203.

[0083] like Figure 7 As described, the imaging system 218 can be positioned 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 techniques, including CT, MRI, fluoroscopy, thermal imaging, ultrasound, OCT, impedance imaging, laser imaging, nanotube X-ray imaging, etc. The imaging system 218 is configured to generate image data of the patient 203 before, during, and / or after the elongated device 231 extends within the patient 203. Therefore, the imaging system 218 can be configured to capture three-dimensional images of the patient 203 before, during, and / or after surgery. In these and other embodiments, the imaging system 218 can provide real-time or near-real-time images of the patient 203.

[0084] Figure 11This describes the elongated device 231 of the medical device system 204 extending within the anatomical region 350, while being captured by the imaging system 218 during the image acquisition period. Figure 8 Such intraoperative image data 680 is a portion 655 of the anatomical region 350. As shown, the image data 680 includes a graphic element 681 representing the elongated device 231 and a graphic element 682 representing the anatomical passage 352 of the anatomical region 350.

[0085] All or a portion of the graphic elements 681 and 682 of image data 680 can be segmented and / or filtered to produce (i) a three-dimensional model of the anatomical passage 352 of a portion 655 of anatomical region 350, and / or (ii) an image point cloud of the elongated device 231 within anatomical region 350. During the segmentation process, pixels or voxels generated from image data 680 can be divided into segments or elements or labeled to indicate that they share certain features or computational properties, such as color, density, intensity, and texture. The segments or elements can then be converted into a model and / or point cloud. Additionally or alternatively, segments or elements can be used to locate (e.g., compute) and / or define a centerline extending along the anatomical passage 352. The resulting anatomical model and / or point cloud can be two-dimensional or three-dimensional and can be displayed in an image reference frame (X). I Y I Z I It is generated in ).

[0086] As mentioned above Figure 6 As discussed, based on data captured and / or generated by the positioning sensor system 108, the endoscopic imaging system 109, the imaging system 118, and / or the virtual visualization system 115, the display system 110 of the medical system 100 can display various images or diagrams of the patient's anatomy and / or the medical device system 104. In various implementations, the system can utilize images and / or diagrams to assist the operator 105 in performing image-guided medical procedures.

[0087] Figure 12 This is a schematic diagram of an example display 710 generated by a display system 110 according to various embodiments of the present technology. As shown, the display 710 includes a real guide image 770, a composite virtual guide image 791 (also referred to as "composite virtual image 791"), and a virtual guide image 792. The real guide image 770 can be compared with... Figure 10 The actual guidance image 570 is substantially the same. Therefore, for example, the actual guidance image 770 can be generated by the endoscopic imaging system 109 ( Figure 7The image is captured and provided to the display system 110 for real-time or near-real-time presentation on the display 710. In the illustrated embodiment, the real guide image 770 illustrates the real patient anatomy, for example, a realistic image of the anatomical passage branching into two bronchi 356 and / or the branching point of the anatomical passage 352 or carina 771 from a perspective oriented distally to the distal portion 237 of the medical device 232.

[0088] Figure 12 The synthesized virtual image 791 is displayed in the image reference frame (X). I Y I Z I ) and includes from the image captured by the imaging system 118 (e.g., Figure 8 The anatomical model 796 is generated from image data of the anatomical region 350. The anatomical model 796 is compared with a point cloud of coordinate points generated by the positioning sensor system 108 (e.g., Figure 9 The point cloud 460) is registered (i.e., dynamically referenced) to be displayed within the anatomical model 796 and the medical device system 104 within the patient 103 (e.g., Figure 7 The illustration 704 shows the tracking of the positioning, shape, posture, orientation, and / or movement of the elongated device 231 in an embodiment. In some embodiments, the synthesized virtual image 791 is controlled by the control system 112 ( Figure 6 The virtual visualization system 115 ( Figure 6 The generation of a synthetic virtual image 791 involves using an image reference frame (X). I Y I Z I ) and surgical reference system (X S Y S Z S ) and / or medical device reference system (X M Y M Z M Registration. This registration can be performed using the coordinates of points in the point cloud captured by the positioning sensor system 108 (e.g., ...). Figure 9 The coordinate points (462) of the point cloud 460 are rotated, translated, or otherwise manipulated by rigid and / or non-rigid transformations to align the coordinate points with the anatomical model 796. Registration between the image and the surgical / instrument reference frame can be achieved, for example, by using the point-based Iterative Nearest Point (ICP) technique described in U.S. Provisional Patent Nos. 62 / 205,440 and 62 / 205,433, both of which are incorporated herein by reference in their entirety. In other embodiments, another point cloud registration technique may be used to achieve registration.

[0089] Based at least in part on this registration, the virtual visualization system 115 may additionally or alternatively generate virtual guidance images (e.g., virtual guidance image 792), which include medical device system 104 within the anatomical model 796. Figure 9 The diagram on Figure 704 shows a virtual depiction of the patient's anatomical structure from the perspective of a virtual camera. Figure 7 The medical device system 204 shown in the figure 704 is in Figure 12 In the embodiment described herein, the virtual camera is positioned at the distal portion 737 of Figure 704 (e.g., of medical device 232), such that (i) the virtual guiding image 792 ( Figure 12 (i) The viewpoint is oriented distally away from the distal portion 737 of the figure 704 and (ii) the figure 704 is not visible within the virtual guidance image 792. In other embodiments, the virtual visualization system 115 may (i) position the virtual camera at another location along the figure 704 and / or (ii) at a different orientation, such that the virtual guidance image 792 has a corresponding virtual viewpoint. In some embodiments, depending on the positioning and orientation of the virtual camera and the positioning of the elongated device 231 and the medical device 232 relative to each other when they are within the patient 103, the virtual visualization system 115 may render a virtual illustration (not shown) of at least a portion of the elongated device 231 and / or the medical device 232 into the virtual guidance image 792.

[0090] In some embodiments, the virtual guide image 792 may optionally include a guide bar 799. In some implementations, for example, the guide bar 799 is used to assist the operator 105 in guiding the medical device system 104 through anatomical pathways to a target location within the patient 103. For example, the guide bar 799 may illustrate an “optimal” path through the patient’s anatomy for the operator 105 to follow in order to deliver the distal portion 237 of the medical device 232 and / or the distal portion 238 of the elongated device 231 to the target location within the anatomical region, respectively. In some embodiments, the guide bar 799 may be aligned with a centerline or another line along the respective anatomical pathway (e.g., its bottom).

[0091] In some embodiments, the virtual visualization system 115 can place a virtual camera within the anatomical model 796 at a location and orientation corresponding to the location and orientation of the image capture device 247 within the patient 103. For example... Figure 12 Additionally, the virtual guide image 792 illustrates a virtual patient anatomy at substantially the same location as the real guide image 770 captured by the image capture device 247. For example, it shows the ridge 701 at the branching point of the two anatomical passages 752 marked on the anatomical model 796. Therefore, the virtual guide image 792 in... Figure 8The virtual guide image 792 provides a rendered estimate of the patient's anatomical structures visible to the image capture device 247 at a given location within the anatomical region 350. Because the virtual guide image 792 is based on registration of a point cloud generated by the positioning sensor system 108 and image data captured by the imaging system 118, the correspondence between the virtual guide image 792 and the real guide image 770 provides accuracy and / or efficiency regarding registration and can be used to improve registration, as described in more detail below. Furthermore, the real guide images captured by the endoscopic imaging system 109 (e.g., real guide images 570 and 770) can (a) provide information about the location and orientation of the medical device system 104 within the patient 103, (b) provide information about portions of the anatomical region actually accessed by the medical device system, and / or (c) help identify patient anatomical structures (e.g., branching points or protuberances of anatomical passages) near the medical device system 104, any one or more of which can be used to improve the accuracy and / or efficiency of registration, as described in more detail below.

[0092] Example

[0093] Several aspects of this technology are illustrated in the following examples. Although several aspects of this technology are illustrated in the examples relating to systems, computer-readable media, and methods, any of these aspects may be similarly illustrated in the examples relating to any systems, computer-readable media, and methods in other embodiments.

[0094] In some embodiments of the present technology (Example 1), a system for mitigating oversampling of data points includes: a medical device including a sensor, wherein the medical device is insertable into an anatomical channel of a patient, such that the sensor is operable to detect one or both of the positioning and movement of the medical device when inserted into the anatomical channel; and a computing device in communication with the medical device, the computing device including a processor and a memory coupled to the processor and storing instructions, which, when executed by the processor, cause the system to perform an operation including: receiving data points detected by the sensor of the medical device, the received data points being correlated with the... The medical device associates one or both of detected positioning and detected motion; analyzes the received set of data points to determine motion parameters associated with the movement or positional change of the sensor of the medical device in the region of the anatomical passage, wherein the motion parameters include changes in one or both of the translational and rotational motion of the sensor; compares the motion parameters with a threshold to determine whether to accept the set of data points when the motion parameters meet the threshold, or to reject the set of data points when the motion parameters do not meet the threshold; and records the accepted set of data points in an examination point cloud that can be used to register the medical device in anatomical reference space.

[0095] Example 2 includes a system according to any one of Examples 1, 3, 4 or 5, wherein the sensor is configured to generate one or both of positioning sensor data and motion sensor data during data sampling in the anatomical passage of the patient, wherein the positioning sensor data is associated with one or more positioning of the medical device within the anatomical passage, 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 anatomical passage.

[0096] Example 3 includes a system according to any one of Examples 1, 2, 4 or 5, wherein the change in one or both of the translational and rotational motions of the sensor includes a change in one or more of (i) roll value, (ii) pitch value or (iii) yaw value.

[0097] Example 4 includes a system according to any one of Examples 1, 2, 3 or 5, wherein the threshold includes a motion value or a range of motion values ​​associated with one or both of the translational motion and the rotational motion of the sensor.

[0098] Example 5 includes a system according to any one of Examples 1, 2, 3 or 4, wherein the system is configured to perform additional operations including generating registration between the received data point set in the checkpoint cloud and image data points derived from previously obtained images of the anatomical passage of the patient.

[0099] In some embodiments of the present technology (Example 6), a system for mitigating oversampling of data points includes: a medical device including sensors, wherein the medical device is insertable into an anatomical channel of a patient, such that the sensors are operable to detect one or both of the positioning and movement of the medical device when inserted into the anatomical channel; and a computing device communicating with the medical device, the computing device including a processor and a memory coupled to the processor and storing instructions, which, when executed by the processor, cause the system to perform operations including: receiving data points detected by the sensors of the medical device, the received data points being associated with a detected positioning of the medical device; analyzing the received data points to determine a distance parameter associated with a distance between the data points and one or more nearest neighbors of the data points; comparing the distance parameter with a threshold to determine whether to accept the data points among the received data points when the distance parameter meets the threshold, or to reject the data points among the received data points when the distance parameter does not meet the threshold; and recording the accepted data points in a checkpoint cloud capable of registering the medical device in an anatomical reference space.

[0100] Example 7 includes a system according to any one of Examples 6, 8, 9 or 10, wherein the threshold includes a distance value or a range of distance values.

[0101] Example 8 includes a system according to any one of Examples 6, 7, 9 or 10, wherein the received data points are initially recorded in the checkpoint cloud, and recording the received data points in the checkpoint cloud includes deleting rejected data points that do not meet the threshold.

[0102] Example 9 includes a system according to any one of Examples 6, 7, 8 or 10, wherein the system is configured to perform additional operations including storing received data points in a temporary storage device and deleting rejected data points from the temporary storage device that do not meet the threshold.

[0103] Example 10 includes a system according to any one of Examples 6, 7, 8 or 9, wherein the system is configured to perform additional operations including generating registration between recorded non-rejected data points in the checkpoint cloud and image data points derived from previously acquired images of the anatomical passage of the patient.

[0104] In some embodiments (Example 11) according to the present technology, a system for mitigating oversampling of data points includes: a medical device including sensors, wherein the medical device is insertable into an anatomical channel of a patient, such that the sensors are operable to detect one or both of the positioning and movement of the medical device when inserted into the anatomical channel; and a computing device in communication with the medical device, the computing device including a processor and a memory coupled to the processor and storing instructions, which, when executed by the processor, cause the system to perform operations including: receiving data points detected by the sensors of the medical device, the received data points being associated with a detected position of the medical device; analyzing the received data points to determine a density parameter associated with the density of one or more data points of nearest neighbor data points; comparing the density parameter with a threshold to determine whether to accept the one or more data points of the analyzed data points when the density parameter meets the threshold, or to reject the one or more data points when the density parameter does not meet the threshold; and recording the accepted data points in a checkpoint cloud capable of registering the medical device in an anatomical reference space.

[0105] Example 12 includes a system according to any one of Examples 11, 13, 14 or 15, wherein the threshold includes a density value or a density value range.

[0106] Example 13 includes a system according to any one of Examples 11, 12, 14 or 15, wherein the received data points are initially recorded in the checkpoint cloud, and recording the received data points in the checkpoint cloud includes deleting rejected data points that do not meet the threshold.

[0107] Example 14 includes a system according to any one of Examples 11, 12, 13 or 15, wherein the system is configured to perform additional operations including storing received data points in a temporary storage device and deleting rejected data points from the temporary storage device that do not meet the threshold.

[0108] Example 15 includes a system according to any one of Examples 11, 12, 13 or 14, wherein the system is configured to perform additional operations including generating registration between recorded non-rejected data points in the checkpoint cloud and image data points derived from previously acquired images of the anatomical passage of the patient.

[0109] In some embodiments of the present technology (Example 16), a system for mitigating oversampling of data points includes: a medical device including sensors, wherein the medical device is insertable into an anatomical channel of a patient, such that the sensors are operable to detect one or both of the positioning and movement of the medical device when inserted into the anatomical channel; and a computing device in communication with the medical device, the computing device including a processor and a memory coupled to the processor and storing instructions, which, when executed by the processor, cause the system to perform operations including: receiving data points detected by the sensors of the medical device, the received data points being associated with a detected positioning of the medical device; analyzing the received data points to determine a density parameter associated with the density of one or more data points of nearest neighbor data points; comparing the density parameter with a threshold to determine whether to change the weighting of the one or more data points within the analyzed data points; changing the weighting of the one or more data points when the density parameter satisfies the threshold; and recording the data points to register the medical device in an anatomical reference space.

[0110] Example 17 includes a system according to any one of Examples 16, 18, 19 or 20, wherein the threshold includes a density value or a density value range.

[0111] Example 18 includes a system according to any one of Examples 16, 17, 19 or 20, wherein changing the weighted value includes normalizing the weighted value.

[0112] Example 19 includes a system according to any one of Examples 16, 17, 18, or 20, wherein the system is configured to perform additional operations including generating registration between recorded non-rejected data points in the checkpoint cloud and image data points derived from previously acquired images of the anatomical passage of the patient.

[0113] Example 20 includes a system according to any one of Examples 16, 17, 18 or 19, wherein the anatomical passage includes the pulmonary airway passage of the lung.

[0114] in conclusion

[0115] The above detailed description of embodiments of this technology is not intended to be exhaustive or to limit the technology to the precise forms disclosed above. Although specific embodiments and examples of the technology have been described above for illustrative purposes, various equivalent modifications can be made within the scope of this technology, as will be recognized by those skilled in the art. For example, although the steps are presented in a given order, alternative embodiments may perform the steps in a different order. Furthermore, the various embodiments described herein may be combined to provide other embodiments.

[0116] The subject matter and functional operations described in this patent document can be implemented in various systems, digital electronic circuit systems, or computer software, firmware, or hardware, including the structures disclosed in this specification and their structural equivalents, or combinations thereof. 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 control of the operation of a data processing device. The computer-readable medium can be a machine-readable storage device, a machine-readable storage substrate, a memory device, a composition of substances affecting machine-readable propagation signals, or combinations thereof. The terms "data processing unit" or "data processing device" encompass all devices, apparatuses, and machines for processing data, including, for example, programmable processors, computers, or multiple processors or computers. In addition to hardware, the device may also include code that creates an execution environment for the computer program in question, for example, code constituting processor firmware, a protocol stack, a database management system, an operating system, or combinations thereof.

[0117] A computer program (also known as a program, software, software application, script, or code) can be written in any programming language, including compiled or interpreted languages, and can be deployed in any form, including as a standalone 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 as part of a file containing other programs or data (e.g., one or more scripts stored in a markup language document), a single file dedicated to the program in question, or multiple coordinating files (e.g., a file storing one or more modules, subroutines, or portions of code). A computer program can be deployed to execute on a single computer or on multiple computers located at a site or distributed across multiple sites and interconnected by a communication network.

[0118] The processes and logic flows described in this specification can be executed by one or more programmable processors that execute one or more computer programs to perform functions by manipulating input data and producing output. The processes and logic flows can also be executed by special-purpose logic circuitry such as FPGAs (Field-Programmable Gate Arrays) or ASICs (Application-Specific Integrated Circuits), and the device can also be implemented as a system of such special-purpose logic circuitry.

[0119] Processors suitable for executing computer programs include, for example, general-purpose and special-purpose microprocessors, and any one or more processors of any type of digital computer. Typically, a processor receives instructions and data from read-only memory or random access memory, or both. The basic components of a computer are a processor for executing instructions and one or more memory devices for storing instructions and data. Typically, a computer will also include one or more mass storage devices (e.g., magneto-optical, magneto-optical, or optical disc) operatively coupled to receive data from or transfer data to, or both, data for storing data. However, a computer does not require such devices. Computer-readable media suitable for storing computer program instructions and data include all forms of non-volatile memory, media, and memory devices, including, for example, semiconductor memory devices such as EPROM, EEPROM, and flash memory devices. The processor and memory may be complemented by or integrated into a dedicated logic circuit system.

[0120] As can be understood from the foregoing, specific embodiments of the technology have been described herein for illustrative purposes, but well-known structures and functions have not been shown or described in detail to avoid unnecessarily obscuring the description of the embodiments. To the extent that any material incorporated herein by reference conflicts with this disclosure, this disclosure shall prevail. Where the context permits, singular or plural terms may also include plural or singular terms respectively. Furthermore, unless the word “or” is explicitly limited to referring only to a single item excluding other items in a list involving two or more items, its use in such a list shall be construed as including (a) any single item in the list, (b) all items in the list, or (c) any combination of items in the list. As used herein, the phrase “and / or” in “A and / or B” refers to A alone, B alone, and both A and B. Where the context permits, singular or plural terms may also include plural or singular terms respectively. Furthermore, the terms “comprising,” “including,” “having,” and “with” are used throughout to indicate that at least one or more of the listed features are included, such that no further number of the same features and / or other types of other features are excluded.

[0121] 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, "substantially" closing an object means that the object is either completely closed or nearly completely closed. In some cases, the exact permissible deviation from absolute completeness may depend on the specific circumstances. However, in general, a degree of near-completeness will have the same overall result as achieving absolute or complete completeness. When used in a negative sense, the use of "substantially" also applies to the complete or nearly complete lack of an action, characteristic, property, state, structure, item, or result.

[0122] From the foregoing, it will also be understood that various modifications can be made without departing from the present technology. For example, the various components of the technology can be further divided into sub-components, or the various components and functions of the technology can be combined and / or integrated. Furthermore, although advantages associated with certain embodiments of the present technology have been described in the context of those embodiments, other embodiments may also exhibit such advantages, and not all embodiments must exhibit such advantages to fall within the scope of the present technology. Therefore, this disclosure and related technologies can cover other embodiments not explicitly shown or described herein.

Claims

1. A system for mitigating oversampling of data points, the system comprising: A medical device including sensors, wherein the medical device is insertable into a patient’s anatomical passage, such that the sensors are operable to detect one or both of the positioning and movement of the medical device when inserted into the anatomical passage. and A computing device communicating with the medical device, the computing device including a processor and a memory coupled to the processor and storing instructions, which, when executed by the processor, cause the system to perform operations including: The medical device receives data points detected by its sensors, and the received data points are associated with one or both of the detected positioning and detected motion of the medical device. Analyze the received set of data points to determine motion parameters associated with changes in the movement or positioning of the sensor of the medical device in the region of the anatomical passage, wherein determining the motion parameters includes determining changes in the translational or rotational motion of the sensor; The change in the translational or rotational motion of the sensor is compared with a threshold to determine whether each corresponding data point in the data point group is accepted when the change in the translational or rotational motion of the sensor meets the threshold, or each corresponding data point in the data point group is rejected when the change in the translational or rotational motion of the sensor does not meet the threshold. and The received data point set is recorded in the checkpoint cloud that can be used to register the medical device in anatomical reference space.

2. The system according to claim 1, wherein, The sensor is configured to generate one or both of positioning sensor data and motion sensor data during data sampling in the anatomical passage of the patient, wherein the positioning sensor data is associated with one or more locations of the medical device within the anatomical passage, and wherein the motion sensor data is associated with one or both of the translational and rotational movements of the medical device within the anatomical passage.

3. The system according to claim 1 or claim 2, wherein, The change in one or both of the translational and rotational motions of the sensor includes a change in one or more of (i) roll value, (ii) pitch value, or (iii) yaw value.

4. The system according to claim 1 or claim 2, wherein, The threshold includes a range of motion values ​​or motion values ​​associated with one or both of the translational and rotational motions of the sensor.

5. The system according to claim 1 or claim 2, wherein, The system is configured to perform additional operations, including generating registration between the received set of data points in the checkpoint cloud and image data points derived from previously acquired images of the patient's anatomical pathway.

6. A system for mitigating oversampling of data points, the system comprising: A medical device including sensors, wherein the medical device is insertable into a patient’s anatomical passage, such that the sensors are operable to detect one or both of the positioning and movement of the medical device when inserted into the anatomical passage. and A computing device communicating with the medical device, the computing device including a processor and a memory coupled to the processor and storing instructions, which, when executed by the processor, cause the system to perform operations including: The system receives data points detected by the sensors of the medical device, and the received data points are associated with the location detected by the medical device. Identify the first data point among the received data points; During the reception of the data points, distance parameters associated with the distance between the first data point and one or more nearest neighbors of the first data point are determined in real time. During the reception of the data points, the distance parameter is compared with a threshold in real time to determine whether the first data point among the received data points is accepted when the distance parameter meets the threshold, or the first data point among the received data points is rejected when the distance parameter does not meet the threshold. and During the reception of the data points, the received data points are recorded in real time in an examination point cloud that can be used to register the medical device in anatomical reference space.

7. The system according to claim 6, wherein, The threshold includes a distance value or a range of distance values.

8. The system according to claim 6, wherein, The received data points are initially recorded in the checkpoint cloud, and recording the received data points in the checkpoint cloud includes deleting rejected data points that do not meet the threshold.

9. The system according to any one of claims 6-8, wherein, The system is configured to perform additional operations, including storing the received data points in a temporary storage device and deleting rejected data points from the temporary storage device that do not meet the threshold.

10. The system according to any one of claims 6-8, wherein, The system is configured to perform additional operations, including generating registration between recorded non-rejected data points in the checkpoint cloud and image data points derived from previously acquired images of the patient's anatomical pathway.

11. A system for mitigating oversampling of data points, the system comprising: A medical device including sensors, wherein the medical device is insertable into a patient’s anatomical passage, such that the sensors are operable to detect one or both of the positioning and movement of the medical device when inserted into the anatomical passage. and A computing device communicating with the medical device, the computing device including a processor and a memory coupled to the processor and storing instructions, which, when executed by the processor, cause the system to perform operations including: The system receives data points detected by the sensors of the medical device, and the received data points are associated with the location detected by the medical device. The received data points are analyzed to determine a density parameter associated with the density of one or more data points to their nearest neighbors, wherein the density parameter is determined by calculating a set of nearest neighbor distances for each of the one or more data points; The density parameter is compared with a threshold to determine whether to accept one or more data points from the analyzed data points when the density parameter meets the threshold, or to reject one or more data points when the density parameter does not meet the threshold. and The received data points are recorded in a checkpoint cloud that can be used to register the medical device in anatomical reference space.

12. The system according to claim 11, wherein, The threshold includes a density value or a density value range.

13. The system according to claim 11, wherein, The received data points are initially recorded in the checkpoint cloud, and recording the received data points in the checkpoint cloud includes deleting rejected data points that do not meet the threshold.

14. The system according to any one of claims 11-13, wherein, The system is configured to perform additional operations, including storing the received data points in a temporary storage device and deleting rejected data points from the temporary storage device that do not meet the threshold.

15. The system according to any one of claims 11-13, wherein, The system is configured to perform additional operations, including generating registration between recorded non-rejected data points in the checkpoint cloud and image data points derived from previously acquired images of the patient's anatomical pathway.

16. A system for mitigating oversampling of data points, the system comprising: A medical device including sensors, wherein the medical device is insertable into a patient’s anatomical passage, such that the sensors are operable to detect one or both of the positioning and movement of the medical device when inserted into the anatomical passage. and A computing device communicating with the medical device, the computing device including a processor and a memory coupled to the processor and storing instructions, which, when executed by the processor, cause the system to perform operations including: The system receives data points detected by the sensors of the medical device, and the received data points are associated with the location detected by the medical device. Analyze the received data points to determine density parameters associated with the density of one or more data points from the nearest neighbor; The density parameter is compared with a threshold to determine whether to change the weighting of one or more data points within the analyzed data points; When the density parameter meets the threshold, the weighting value of the one or more data points is changed; and The data points are recorded to register the medical device in anatomical reference space.

17. The system according to claim 16, wherein, The threshold includes a density value or a density value range.

18. The system according to claim 16, wherein, Changing the weighted values ​​includes normalizing the weighted values.

19. The system according to any one of claims 16-18, wherein, The system is configured to perform additional operations, including generating registration between recorded, unrejected data points and image data points derived from previously acquired images of the patient's anatomical passage.

20. The system according to any one of claims 16-18, wherein, The anatomical passage includes the lung airway passage.

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