Automated tool for vein reduction in anatomical maps

Abstract

An automated technique for correcting an electroanatomical map generated using a catheter having a plurality of electrodes is disclosed. A first electroanatomical map including an anatomical structure having a mapping volume with a substantially tubular shape is displayed, and one or more points along a median axis of the mapping volume are estimated. At a first cross-section of the mapping volume, a first best fit ellipse is determined. A generalized cylindrical volume between the first cross-section and the second cross-section is calculated from at least the first best fit ellipse. Data points outside of the generalized cylindrical volume are removed from the mapping volume, and a modified mapping map is displayed.

Description

Technical Field

[0001] The present invention relates to anatomical mapping. More particularly, the present invention relates to improving the visualization of anatomical structures, such as veins, in electroanatomical maps. Background Art

[0002] Some clinical procedures use technology for analyzing computerized anatomical maps of organs. For example, in electrophysiology (EP) procedures, such as catheter-based radiofrequency (RF) ablation for pulmonary vein isolation (the first line treatment for atrial fibrillation (AF)), anatomical maps of the heart chambers are generated and used. Fast Anatomical Mapping (FAM) is an algorithm for establishing such anatomical maps based on electrical signals captured by a catheter on the myocardium. The anatomical map is used to guide the physician to the desired ablation site. As part of constructing the anatomical map (e.g., one aspect of generating the anatomical map of the FAM), a technician can modify the volume of the FAM by performing a manual, time-consuming reduction process. Reduction occurs for various reasons, including, for example, to present a more anatomically accurate representation and / or to resolve visual artifacts in the map.

[0003] Using existing mapping techniques, artifacts of the mapping process can cause anatomical structures, such as veins, to appear narrow in one portion of the vein and larger in an adjacent portion of the vein. This visualization can suggest the presence of pulmonary vein stenosis at the site where the vein is narrow. To remove such artifacts, manual trimming of the map is typically performed by the operator. When dealing with artifacts such as those described above (implying pulmonary vein stenosis), voxels are manually removed (trimmed) from the vein volume until the vein has a more constant volume. An automated solution to this manual trimming process is needed. Summary of the Invention

[0004] An automated technique for correcting an electroanatomical map (e.g., a FAM) is provided. The map is generated using a catheter having a plurality of electrodes. As the catheter moves within the body during a medical procedure, the map is generated based on data points acquired using the electrodes and subsequently corrected. Initially, a first electroanatomical map including an anatomical structure having a mapping volume with a substantially tubular shape is displayed on a user interface. At a first cross-section of the mapping volume, a first best-fit ellipse is determined based on data points associated with the first cross-section of the mapping volume. A first point along a medial axis of the mapping volume is estimated based on the center of the first best-fit ellipse. A second point along the medial axis is estimated at a second cross-section of the mapping volume; the first cross-section is different from the second cross-section. A generalized cylindrical volume spanning between the first cross-section and the second cross-section is calculated based on at least the first best-fit ellipse. Data points outside the generalized cylindrical volume are removed from the mapping volume. A second electroanatomical map having an updated version of the anatomical structure generated without the removed data points is displayed on the user interface.

[0005] In some examples, a plurality of points defining the median axis are determined. In some of these examples, the first cross-section is perpendicular to the median axis, and the second point is estimated by selecting one of the plurality of points defining the median axis.

[0006] In some examples, additional points along the median axis are estimated at additional cross-sections of the mapping volume, and the generalized cylindrical volume spans the first cross-section, the second cross-section, and the additional cross-section.

[0007] In some examples, the anatomical structure is a vein associated with the myocardium, the data points associated with the first cross-section of the mapping volume correspond to ablation labels, and the data points associated with the second cross-section and each of the additional cross-sections of the mapping volume do not correspond to ablation labels.

[0008] In some examples, more than two best-fit ellipses are determined based on data points associated with other cross-sections of the mapping volume, and the generalized cylindrical volume is calculated based on the more than two best-fit ellipses.

[0009] In some examples, the first best fit ellipse is a circle, and the substantially tubular shape is a ruled surface or a generalized cylinder. In other embodiments, a best fit spline is used.

[0010] According to one or more implementations, the above-described exemplary embodiments may be implemented as a method, apparatus, system, and / or computer program product. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] A more detailed understanding may be obtained from the following detailed description provided by way of example in conjunction with the accompanying drawings, in which like reference numerals indicate like elements, and in which:

[0012] Figure 1 depicts an example catheter-based electrophysiological mapping and ablation system according to one or more embodiments;

[0013] Figure 2 is a block diagram of an example system for remotely monitoring and transmitting biometric data according to one or more embodiments;

[0014] Figure 3 is a system diagram of an example computing environment in communication with a network according to one or more embodiments;

[0015] Figure 4 is a block diagram of an example device that may implement one or more features of the present disclosure, according to one or more embodiments;

[0016] Figure 5A depicts an electroanatomical map of a heart before performing anatomical structure fitting for ablation tags according to an example;

[0017] Figure 5B depicts an electroanatomical map of a heart after performing anatomical structure fitting for ablation tags according to an example;

[0018] Figure 6 An electroanatomical map of the heart and its medial axis according to an example is depicted;

[0019] Figure 7 depicts an electroanatomical map of the pulmonary veins showing a median axis of the pulmonary veins and several best-filled ellipses positioned along the median axis, according to an example;

[0020] Figure 8 Depicts a method for generating a Figure 7 The median axis of the pulmonary vein is a tubular shape of several ellipses;

[0021] Figure 9 depicts a tubular shape for removing data points from a map according to an example;

[0022] Figure 10 Depicted according to the example Figure 5B a side-by-side comparison of a map of FIG. 1 with an updated version of the map that has been revised according to the techniques described herein;

[0023] Figure 11 depicts an electroanatomical map of a heart according to another example; and

[0024] Figure 12Methods according to one or more embodiments are described. DETAILED DESCRIPTION

[0025] Disclosed herein is a method and / or system for anatomical mapping. The method and / or system includes processor executable code or software that must be embedded in processing operations performed by a medical device that performs and uses anatomical mapping, as well as in the processing hardware of the medical device. For ease of explanation, anatomical mapping is described herein with respect to mapping the heart. However, any anatomical structure, body part, organ, or portion thereof can be a target for mapping using the techniques described herein.

[0026] According to one or more embodiments, methods and systems disclosed herein generate an anatomical map of the heart, including the endocardial surface of the left atrium (LA). The map can be a three-dimensional (3D) model or a combination of multiple 3D models. The methods and systems can generate and edit maps of the heart and provide real-time or post-processing maps during or in conjunction with an EP procedure (e.g., an ablation procedure). For example, the methods and systems can use the techniques disclosed herein to modify the anatomical map, thereby improving the operation and results of anatomical mapping.

[0027] refer to Figure 1 , which illustrates an example system (e.g., a medical device assembly and / or a catheter-based electrophysiological mapping and ablation system), shown as system 10, in which one or more features of the subject matter herein may be implemented according to one or more embodiments. All or part of system 100 may be used to collect information (e.g., biometric data) and / or to implement map correction techniques as described herein. In some examples, such techniques are implemented using processor-executable code or software that is stored on a memory of system 10 and that must originate from processing operations of system 10 or processing hardware of the system.

[0028] System 1 shows a recorder 11, a heart 12, a catheter 14, a model or anatomical map 20, an electrogram 21, a spine 22, a patient 23, a physician 24 (which represents any medical professional, technician, clinician, operator, clinical support specialist, clinical account specialist, paramedic, etc.), a location pad 25, one or more electrodes 26, a display device 27, a distal tip 28, a sensor 29, a coil 32, a patient interface unit (PIU) 30, an electrode skin patch 38, an ablation energy generator 50, and a workstation 55. Note also that each element and / or item of system 10 represents one or more of that element and / or item. Figure 1The example of system 10 shown implements the embodiments disclosed herein. The embodiments disclosed herein can be similarly applied using other system components and configurations. In addition, system 10 can include additional components, such as elements for sensing electrical activity, wired or wireless connectors, processing and display devices, or other components.

[0029] The system 10 includes a plurality of catheters 14 that are inserted percutaneously through the patient's vascular system into a chamber or vascular structure of the heart 12 by a physician 24. Typically, a delivery sheath catheter is inserted into the left or right atrium near a desired location in the heart 12. Thereafter, a plurality of catheters may be inserted into the delivery sheath catheter to reach the desired location. The plurality of catheters 14 may include catheters dedicated to sensing intracardiac electrogram (IEGM) signals, catheters dedicated to ablation, and / or catheters dedicated to both sensing and ablation. An example catheter 14 configured for sensing IEGM is shown herein. The physician 24 brings the distal tip 28 of the catheter 14 into contact with the heart wall for sensing a target site in the heart 12. For ablation, the physician 24 would similarly bring the distal end of the ablation catheter to the target site for ablation.

[0030] The catheter 14 is an exemplary catheter that includes at least one (preferably multiple) electrodes 26 that are optionally distributed on a plurality of splines 22 at a distal tip 28 and configured to sense IEGM signals. In addition, the catheter 14 may also include a sensor 29 that is embedded in or near the distal tip 28 for tracking the position and orientation of the distal tip 28. Optionally and preferably, the position sensor 29 is a magnetic-based position sensor that includes three magnetic coils for sensing 3D position and orientation. According to one or more embodiments, the shape and parameters of the catheter 14 vary based on whether the catheter 14 is used for diagnostic or ablation purposes, the type of arrhythmia, the patient's anatomy, and other factors that affect the maneuverability of the catheter (e.g., the ability to touch without bending the surface and tracked portion of the catheter 14). The shape and parameters of the catheter 14 also affect the accuracy of the anatomical map. Large, spherical, single-shot catheters that can ablate pulmonary veins in seconds have become popular, but require guidance from fluoroscopy, CT / MRI, or an additional mapping catheter.

[0031] A sensor 29 (e.g., a position-based or magnetic sensor) can operate in conjunction with a position mat 25 that includes a plurality of magnetic coils 32 configured to generate a magnetic field in a predefined workspace. The real-time position of the distal tip 28 of the catheter 14 can be tracked based on the magnetic field generated by the position mat 25 and sensed by the sensor 29. Details of magnetic-based position sensing technology are described in U.S. Patents 5,5391,199, 5,443,489, 5,558,091, 6,172,499, 6,239,724, 6,332,089, 6,484,118, 6,618,612, 6,690,963, 6,788,967, and 6,892,091.

[0032] The system 10 includes one or more electrode patches 38 positioned in contact with the skin of the patient 23 to establish a position reference for impedance-based tracking of the location pad 25 and the electrodes 26. For impedance-based tracking, current is directed toward the electrodes 26 and sensed at the patches 38 (e.g., electrode skin patches) so that the position of each electrode can be triangulated via the patches 38. Details of impedance-based position tracking technology are described in U.S. Patents 7,536,218, 7,756,576, 7,848,787, 7,869,865, and 8,456,182, which are incorporated herein by reference.

[0033] Recorder 11 displays electrograms 21 captured with electrodes 18 (e.g., surface electrocardiogram (ECG) electrodes) and intracardiac electrograms (IEGMs) captured with electrodes 26 of catheter 14. Recorder 11 may include pacing capabilities for pacing the cardiac rhythm and / or may be electrically connected to a separate pacemaker.

[0034] The system 10 may include an ablation energy generator 50 adapted to conduct ablation energy to one or more of the electrodes 26 at the distal tip 28 of the catheter 14 configured for ablation. The energy generated by the ablation energy generator 50 may include, but is not limited to, radio frequency (RF) energy or pulsed field ablation (PFA) energy (including monopolar or bipolar high voltage DC pulses that may be used to achieve irreversible electroporation (IRE)), or a combination thereof.

[0035] The PIU 30 is an interface configured to establish electrical communication between the catheters, electrophysiology equipment, a power source, and a workstation 55 for controlling the operation of the system 10. The electrophysiology equipment of the system 10 may include, for example, a plurality of catheters 14, location pads 25, surface ECG electrodes 18, electrode patches 38, an ablation energy generator 50, and a recorder 11. Optionally and preferably, the PIU 30 further includes processing capabilities for enabling real-time calculation of the position of the catheters and for performing ECG calculations.

[0036] The workstation 55 includes a memory, a processor unit with memory or storage loaded with appropriate operating software, and user interface capabilities. The workstation 55 can provide multiple functions, optionally including: three-dimensional (3D) modeling of the endocardial anatomy and rendering the model or anatomical map 20 (e.g., visualization) for display on the display device 27; displaying on the display device 27 an activation sequence (or other data) compiled from recorded electrograms 21 as representative visual markers or images superimposed on the rendered anatomical map 20; displaying the real-time position and orientation of multiple catheters within the heart chamber; and displaying on the display device 27 a region of interest, such as where ablation energy has been applied. A commercial product embodying elements of the system 10 may be CARTO TM The 3 system is available from Biosense Webster, Inc., 31A Technology Drive, Irvine, CA 92618. It should be noted that modeling the endocardial anatomy in 3D may include generating its surface as a triangular mesh.

[0037] For example, the system 10 may be a surgical system (e.g., sold by Biosense Webster). The present invention relates to a surgical system (system) that is configured to obtain biometric data (e.g., anatomical measurements and electrical measurements of a patient's organ, such as the heart 12, and as described herein) and to perform cardiac ablation procedures. More specifically, the treatment of cardiac conditions, such as arrhythmias, often requires obtaining detailed mapping of cardiac tissue, chambers, veins, arteries, and / or electrical pathways. For example, a prerequisite for successfully performing catheter ablation is that the cause of the arrhythmia is accurately located in a chamber of the heart 12. Such localization can be accomplished via an electrophysiological study during which electrical potentials are detected and spatially resolved using a mapping catheter (e.g., catheter 14) introduced into a chamber of the heart 12. This electrophysiological study (so-called electroanatomical mapping) thus provides 3D mapping data that can be displayed on the display device 27. In many cases, the mapping function and the therapeutic function (e.g., ablation) are provided by a single catheter or a group of catheters, such that the mapping catheter also operates simultaneously as a therapeutic catheter.

[0038] Figure 2is a block diagram of an example system 100 for remotely monitoring and transmitting biometric data (e.g., patient biometrics). Figure 2 In the example shown, system 100 includes a patient biometric monitoring and processing device 102 associated with a patient 104, a local computing device 106, a remote computing system 108, a first network 110, a patient biometric sensor 112, a processor 114, a user input (UI) sensor 116, a memory 118, a second network 120, and a transmitter-receiver (i.e., transceiver) 122.

[0039] According to one or more embodiments, the patient biometric monitoring and processing device 102 may be a device that is internal to the patient's body (e.g., subcutaneously implantable), such as Figure 1 The patient biometric monitoring and processing device 102 may be inserted into the patient's body via any suitable means, including oral injection, surgical insertion via a vein or artery, an endoscopic procedure, or a laparoscopic procedure.

[0040] According to one or more embodiments, the patient biometric monitoring and processing device 102 may be a device external to the patient's body, e.g. Figure 1 The patient biometric monitoring and processing device 102 may include an electrode patch 38. For example, as described in more detail below, the patient biometric monitoring and processing device 102 may include an attachable patch (e.g., which attaches to the patient's skin). The monitoring and processing device 102 may also include a catheter with one or more electrodes, a probe, a blood pressure cuff, a weight scale, a bracelet or smartwatch biometric tracker, a glucose monitor, a continuous positive airway pressure (CPAP) machine, or virtually any device that can provide input related to the patient's health or biometrics.

[0041] According to one or more embodiments, the patient biometric monitoring and processing device 102 may include both components internal to the patient and components external to the patient.

[0042] Figure 2 1 shows a single patient biometric monitoring and processing device 102. However, the example system may include multiple patient biometric monitoring and processing devices. The patient biometric monitoring and processing device may communicate with one or more other patient biometric monitoring and processing devices. Additionally or alternatively, the patient biometric monitoring and processing device may communicate with a network 110.

[0043] One or more patient biometric monitoring and processing devices 102 can acquire biometric data (e.g., patient biometrics such as electrical signals, blood pressure, temperature, blood glucose levels, or other biometric data) and receive at least a portion of the biometric data representing the acquired patient biometrics and additional information associated with the acquired patient biometrics from one or more other monitoring and processing devices 102. The additional information can be, for example, diagnostic information and / or additional information obtained from an additional device such as a wearable device. Each patient biometric monitoring and processing device 102 can process data including its own biometric data and data received from one or more other patient biometric monitoring and processing devices 102.

[0044] Biometric data (e.g., patient biometrics, patient data, or patient biometric data) may include one or more of local activation time (LAT), electrical activity, topology, bipolar mapping, reference activity, ventricular activity, dominant frequency, impedance, or other data. LAT can be a time point corresponding to a threshold activity of local activation calculated based on a normalized initial starting point. Electrical activity can be any applicable electrical signal that can be measured based on one or more thresholds and can be sensed and / or enhanced based on a signal-to-noise ratio and / or other filters. Topology can correspond to the physical structure of a body part or a portion of a body part, and can correspond to changes in the physical structure relative to different parts of the body part or relative to different body parts. Dominant frequency can be a frequency or frequency range that is prevalent at a part of the body part and can be different in different parts of the same body part. For example, the dominant frequency of the PV of a heart can be different from the dominant frequency of the right atrium of the same heart. Impedance can be a measurement of electrical resistance at a given area of the body part.

[0045] Examples of biometric data include, but are not limited to, patient identification data, intracardiac electrocardiogram (IC ECG) data, bipolar intracardiac reference signals, anatomical and electrical measurements, trajectory information, body surface (BS) ECG data, historical data, brain biometrics, blood pressure data, ultrasound signals, radio signals, audio signals, two-dimensional or three-dimensional image data, blood glucose data, and temperature data. Biometric data can generally be used to monitor, diagnose, and treat any number of various diseases, such as cardiovascular diseases (e.g., arrhythmias, cardiomyopathies, and coronary artery disease) and autoimmune diseases (e.g., type I and type II diabetes). It is noted that BS ECG data may include data and signals collected from electrodes on the surface of the patient, IC ECG data may include data and signals collected from electrodes inside the patient, and ablation data may include data and signals collected from tissue that has been ablated. In addition, BS ECG data, IC ECG data, and ablation data, along with catheter electrode positioning data, may be derived from one or more procedure records.

[0046] exist Figure 2 In the embodiment of the present invention, the network 110 is an example of a short-range network, such as a local area network (LAN) or a personal area network (PAN). Information can be sent between the patient biometric monitoring and processing device 102 and the local computing device 106 via the network 110 using any of a variety of short-range wireless communication protocols, such as Bluetooth, Wi-Fi, Zigbee, Z-Wave, near field communication (NFC), ultraband, or infrared (IR).

[0047] The network 120 may be a wired network, a wireless network, or include one or more wired and wireless networks. For example, the network 120 may be a long-range network (e.g., a wide area network (WAN), the Internet, or a cellular network). Information may be sent via the network 120 using any of a variety of long-range wireless communication protocols (e.g., TCP / IP, HTTP, 3G, 4G / LTE, or 5G / New Radio).

[0048] The patient biometric monitoring and processing device 102 may include a patient biometric sensor 112, a processor 114, a UI sensor 116, a memory 118, and a transceiver 122. The patient biometric monitoring and processing device 102 may continuously or periodically monitor, store, process, and transmit any number of various biometric data via the network 110. Examples of biometric data include electrical signals (e.g., ECG signals and brain biometrics), blood pressure data, blood glucose data, and temperature data. Biometric data may be monitored and transmitted to facilitate treatment of any number of various diseases, such as cardiovascular diseases (e.g., arrhythmias, cardiomyopathy, and coronary artery disease) and autoimmune diseases (e.g., type I and type II diabetes).

[0049] The patient biometric sensors 112 may include, for example, one or more sensors configured to sense biometric data. For example, the patient biometric sensors 112 may include electrodes configured to collect electrical signals (e.g., heart signals, brain signals, or other bioelectrical signals), a temperature sensor, a blood pressure sensor, a blood glucose sensor, a blood oxygen sensor, a pH sensor, an accelerometer, and a microphone.

[0050] As described in more detail below, the patient biometric monitoring and processing device 102 can be an ECG monitor for monitoring ECG signals of a heart (e.g., heart 12). The patient biometric sensor 112 of the ECG monitor can include one or more electrodes for acquiring ECG signals. ECG signals can be used to treat various cardiovascular diseases and for anatomical mapping.

[0051] The transceiver 122 may include a separate transmitter and receiver. Alternatively, the transceiver 122 may include a transmitter and receiver integrated into a single device.

[0052] Processor 114 can be configured to store biometric data acquired by patient biometric sensor 112 in memory 118 and transmit the biometric data across network 110 via a transmitter of transceiver 122. Data from one or more other patient biometric monitoring and processing devices 102 can also be received by a receiver of transceiver 122, as described in greater detail herein. By way of example, the automated map correction techniques described herein are implemented as processor-executable code or software that can be stored on memory 118 (as shown) and executed by processor 114. As another example, the automated map correction techniques are implemented as code stored and executed on local computing device 106 and / or remote computing system 108. Therefore, the operation of the automated map correction techniques must derive from the processing operations of system 100 and the processing hardware of that system.

[0053] According to one or more embodiments, the system 100 is used to generate an initial visualization (e.g., a first electroanatomical map) on a display (e.g., display device 27) during an ablation procedure. The initial visualization is generated based on data points sensed by a catheter positioned in a patient and includes an anatomical structure (e.g., a vein) having a mapping volume with a substantially tubular shape. Figure 12 In the described technique, the system 100 determines a first best fit ellipse at a first cross-section of a mapping volume based on data points associated with the first cross-section. A first point along a medial axis of the mapping volume is estimated based on (e.g., in accordance with) a center of the first best fit ellipse. A second point along the medial axis is estimated at a second cross-section of the mapping volume; the first cross-section is different from the second cross-section. A generalized cylindrical volume spanning between the first cross-section and the second cross-section is calculated based on at least the first best fit ellipse. The system 100 removes data points outside the generalized cylindrical volume from the mapping volume. A second electroanatomical map having an updated version of the anatomical structure generated without the removed data points is displayed (e.g., on the display device 27) as part of a user interface.

[0054] In some examples, the anatomical structure is a vein associated with the myocardium, data points associated with the first cross-section of the mapping volume correspond to ablation labels, and data points associated with the second and additional cross-sections of the mapping volume do not correspond to ablation labels.

[0055] In some examples, a plurality of points defining the median axis are determined. In some of these examples, the first cross-section is perpendicular to the median axis, and the second point is estimated by selecting one of the plurality of points defining the median axis.

[0056] According to one or more embodiments, the patient biometric monitoring and processing device 102 includes a UI sensor 116, which can be, for example, a piezoelectric sensor or a capacitive sensor configured to receive user input (e.g., a tap or touch). For example, in response to the patient 104 tapping or contacting the surface of the patient biometric monitoring and processing device 102, the UI sensor 116 can be controlled to implement capacitive coupling. Gesture recognition can be implemented via any of a variety of capacitance types, such as resistive capacitance, surface capacitance, projected capacitance, surface acoustic wave, piezoelectric, and infrared touch. The capacitive sensor can be positioned in a small area or along the length of the surface so that a tap or touch of the surface activates the monitoring device.

[0057] As described in more detail below, the processor 114 can be configured to selectively respond to different tap patterns (e.g., single or double taps) of the capacitive sensor (which can be the UI sensor 116) so that different tasks of the patch (e.g., data collection, storage, or transmission) can be activated based on the detected pattern. In some embodiments, when a gesture is detected, audible feedback can be given to the user from the patient biometric monitoring and processing device 102.

[0058] The local computing device 106 of the system 100 communicates with the patient biometric monitoring and processing device 102 and can be configured to act as a gateway to the remote computing system 108 via a second network 120. For example, the local computing device 106 can be, for example, a smartphone, a smartwatch, a tablet, or other portable smart device configured to communicate with other devices via the network 120. Alternatively, the local computing device 106 can be a fixed or standalone device, such as a fixed base station including, for example, a modem and / or router capabilities, a desktop or laptop computer using an executable program to transmit information between the patient biometric monitoring and processing device 102 and the remote computing system 108 via the PC's radio module, or a USB dongle. Biometric data can be transmitted between the local computing device 106 and the patient biometric monitoring and processing device 102 via a short-range wireless network 110, such as a local area network (LAN) (e.g., a personal area network (PAN)) using short-range wireless technology standards (e.g., Bluetooth, Wi-Fi, ZigBee, Z-wave, and other short-range wireless standards). In some embodiments, the local computing device 106 may also be configured to display the acquired patient electrical signals and information associated with the acquired patient electrical signals, as described in more detail herein.

[0059] In some embodiments, the remote computing system 108 can be configured to receive at least one of the monitored patient biometric and information associated with the monitored patient via a network 120 as a remote network. For example, if the local computing device 106 is a mobile phone, the network 120 can be a wireless cellular network, and information can be transmitted between the local computing device 106 and the remote computing system 108 via a wireless technology standard, such as any of the wireless technologies described above. As described in more detail below, the remote computing system 108 can be configured to provide (e.g., visually display and / or audibly provide) at least one of the patient biometric and the associated information to the physician 24.

[0060] Figure 3 is a system diagram of an example of a computing environment 200 in communication with network 120. In some cases, computing environment 200 is incorporated into a public cloud computing platform (e.g., Amazon Web Services or Microsoft Azure), a hybrid cloud computing platform (e.g., HP Enterprise OneSphere), or a private cloud computing platform.

[0061] like Figure 3 As shown, computing environment 200 includes computer system 210, which is Figure 1 Workstation 55, Figure 2 The local computing device 106 and / or Figure 2 200 , and is an example of a remote computing system 108 on which the various embodiments described herein may be implemented. By way of example, the bump detection and correction techniques described herein are implemented as processor-executable code or software that may be stored in system memory 231 (as shown) and executed by processor 220 and embodied in processing operations performed by computing environment 200 and in the processing hardware of the computing environment.

[0062] The computer system 210 may perform various functions via a processor 220, which may include one or more processors. The functions may include analyzing monitored biometric data and associated information and providing (e.g., via a display 266) alerts, additional information, or instructions based on thresholds and parameters determined by a physician or driven by an algorithm. These functions may include the operation of the protrusion error and correction techniques described herein. As described in more detail herein, the computer system 210 may be used to provide Figure 1 The physician 24 is provided (e.g., via the display 266) with a patient information dashboard so that such information may enable the physician 24 to identify and prioritize patients with more critical needs than others.

[0063] like Figure 3As shown, computer system 210 may include a communication mechanism (e.g., bus 221) or other communication mechanism for transmitting information within computer system 210. Computer system 210 also includes one or more processors 220 coupled to bus 221 for processing information. Processor 220 may include one or more CPUs, GPUs, or any other processor known in the art.

[0064] Computer system 210 also includes system memory 230, coupled to bus 221, for storing information and instructions to be executed by processor 220. System memory 230 may include computer-readable storage media in the form of volatile and / or non-volatile memory, such as read-only system memory (ROM) 231 and / or random access memory (RAM) 232. System memory RAM 232 may include other dynamic storage devices (e.g., dynamic RAM, static RAM, and synchronous DRAM). System memory ROM 231 may include other static storage devices (e.g., programmable ROM, erasable PROM, and electrically erasable PROM). In addition, system memory 230 may be used to store temporary variables or other intermediate information during the execution of instructions by processor 220. Basic input / output system 233 (BIOS) may include routines for transferring information between components within computer system 210 (e.g., during the startup process), which may be stored in system memory ROM 231. RAM 232 may contain data and / or program modules that are immediately accessible to and / or currently being operated on by processor 220. System memory 230 may additionally include, for example, operating system 234 , application programs 235 , other program modules 236 , and program data 237 .

[0065] The illustrated computer system 210 also includes a disk controller 240 that is coupled to the bus 221 to control one or more storage devices for storing information and instructions, such as a hard disk 241 and a removable media drive 242 (e.g., a floppy disk drive, an optical drive, a tape drive, and / or a solid-state drive). Storage devices can be added to the computer system 210 using an appropriate device interface (e.g., small computer system interface (SCSI), integrated device electronics (IDE), universal serial bus (USB), or FireWire).

[0066] The computer system 210 may also include a display controller 265 coupled to the bus 221 to control a monitor or display 266, such as a cathode ray tube (CRT) or a liquid crystal display (LCD), to display information to a computer user. The illustrated computer system 210 includes a user input interface 260 and one or more input devices, such as a keyboard 262 and a pointing device 261, for interacting with a computer user and providing information to the processor 220. The pointing device 261 may be, for example, a mouse, a trackball, or a pointing stick for communicating directional information and command selections to the processor 220 and for controlling cursor movement on the display 266. The display 266 may provide a touch screen interface that allows input to supplement or replace the communication of directional information and command selections by the pointing device 261 and / or the keyboard 262.

[0067] In response to the processor 220 executing one or more sequences of one or more instructions contained in a memory (e.g., system memory 230), the computer system 210 may perform a portion or each of the functions and methods described herein. Such instructions may be read into the system memory 230 from another computer-readable medium such as (e.g., hard disk 241 or removable media drive 242). The hard disk 241 may contain one or more data repositories and data files used by the embodiments described herein. The data repository contents and data files may be encrypted to increase security. The processor 220 may also be employed in a multi-processing arrangement to execute one or more sequences of instructions contained in the system memory 230. In an alternative embodiment, hard-wired circuitry may be used in place of or in combination with software instructions. Therefore, the embodiments are not limited to any particular combination of hardware circuitry and software.

[0068] As described above, the computer system 210 may include at least one computer-readable medium or memory for storing instructions programmed according to the embodiments described herein (e.g., embodiments of the bump error detection and correction technology) and for containing data structures, tables, records, or other data described herein. The term computer-readable medium, as used herein, refers to any non-transitory tangible medium that participates in providing instructions to the processor 220 for execution. Computer-readable media can take many forms, including but not limited to non-volatile media, volatile media, and transmission media. Non-limiting examples of non-volatile media include optical disks, solid-state drives, magnetic disks, and magneto-optical disks, such as hard disk 241 or removable media drive 242. Non-limiting examples of volatile media include dynamic memory, such as system memory 230. Non-limiting examples of transmission media include coaxial cables, copper wire, and optical fibers, including the wires that make up bus 221. Transmission media can also take the form of acoustic or light waves, such as those generated during radio wave and infrared data communications.

[0069] The computing environment 200 may also include a computer system 210 that operates in a networked environment using logical connections to the local computing device 106 and one or more other devices, such as personal computers (laptops or desktops), mobile devices (e.g., patient mobile devices), servers, routers, network PCs, peer devices, or other public network nodes, and typically includes many or all of the elements described above with respect to the computer system 210. When used in a networked environment, the computer system 210 may include a modem 272 for establishing communications over the network 120 (e.g., the Internet). The modem 272 may be connected to the system bus 221 via a network interface 270 or via another appropriate mechanism.

[0070] like Figure 2 and Figure 3 As shown, network 120 can be any network or system known in the art, including the Internet, an intranet, a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), a direct connection or a series of connections, a cellular telephone network, or any other network or medium capable of facilitating communication between computer system 210 and other computers (e.g., local computing device 106).

[0071] Figure 4 4 is a block diagram of an example device 400 that may implement one or more features of the present disclosure. For example, device 400 may be local computing device 106. Device 400 may include, for example, a computer, a gaming device, a handheld device, a set-top box, a television, a mobile phone, or a tablet computer. Device 400 includes a processor 402, a memory 404, a storage device 406, one or more input devices 408, and one or more output devices 410. Device 400 may also optionally include an input driver 412 and an output driver 414. It should be understood that device 400 may include Figure 4 Additional components not shown include artificial intelligence accelerators.

[0072] In various alternatives, the processor 402 includes a central processing unit (CPU), a graphics processing unit (GPU), a CPU and a GPU on the same die, or one or more processor cores, where each processor core can be a CPU or a GPU. In various alternatives, the memory 404 is located on the same die as the processor 402 or is located separately from the processor 402. The memory 404 includes volatile or non-volatile memory, such as random access memory (RAM), dynamic RAM, or a cache. By way of example, the map correction techniques described herein are implemented as processor executable code or software that can be stored on the memory 404 (as shown) and executed by the processor 402 and is derived from processing operations performed by the example device 400 and from the processing hardware of the example device.

[0073] Storage device 406 includes fixed or removable storage devices, such as a hard drive, solid-state drive, optical disk, or flash drive. Input device 408 includes, but is not limited to, a keyboard, a keypad, a touch screen, a touchpad, a detector, a microphone, an accelerometer, a gyroscope, a biometric scanner, or a network connection (e.g., a wireless LAN card for transmitting and / or receiving wireless IEEE 802 signals). Output device 410 includes, but is not limited to, a display device, a speaker, a printer, a tactile feedback device, one or more lights, an antenna, or a network connection (e.g., a wireless LAN card for transmitting and / or receiving wireless IEEE 802 signals).

[0074] Input driver 412 communicates with processor 402 and input device 408 and allows processor 402 to receive input from input device 408. Output driver 414 communicates with processor 402 and output device 410 and allows processor 402 to send output to output device 410. Note that input driver 412 and output driver 414 are optional components, and device 400 would operate in the same manner if input driver 412 and output driver 414 were not present. Output driver 414 includes accelerated processing device (“APD”) 416, which communicates with a display device, such as represented by output device 410. APD 416 accepts computational commands and graphics rendering commands from processor 402, processes those computational and graphics rendering commands, and provides pixel output to the display device for display. As described in further detail below, APD 416 includes one or more parallel processing units to perform computations according to a single instruction, multiple data (“SIMD”) paradigm. Thus, although various functions are described herein as being performed by or in conjunction with APD 416, in various alternatives, the functions described as being performed by APD 416 may additionally or alternatively be performed by other computing devices having similar capabilities that are not driven by a host processor (e.g., processor 402) and that provide graphical output to a display device. For example, it is contemplated that any processing system that performs processing tasks according to the SIMD paradigm may perform the functions described herein. Alternatively, it is contemplated that computing systems that do not perform processing tasks according to the SIMD paradigm may perform the functions described herein.

[0075] Figure 5A An electroanatomical map of a heart 500 is depicted before performing anatomical structure fitting for ablation tags according to an example. The heart 500 includes a pulmonary vein 502 extending along a length 504a. The vein 502 has a substantially tubular shape along the length 504a. Figure 5A , the substantially tubular shape of the vein 502 has a cross-sectional dimension that exhibits variations along the length 504a that are consistent with a normal (healthy) vein. The electroanatomical map also includes a plurality of labels 501. An example of a label 501 is an ablation label that objectively identifies and annotates a location on the electroanatomical map whenever a predefined criterion (such as catheter stability, time, contact force, or impedance drop) is met. An example of an ablation label is the CARTO VISITAG sold by Biosense Webster. TMThe system provides. In an embodiment of the system, the system calculates an index called the ablation label index, which is a numerical value that reflects the quality and effectiveness of ablation at a specific location. The index helps the electrophysiologist assess whether enough tissue has been treated to achieve the desired treatment effect. The system is often integrated with a 3D mapping system that allows the electrophysiologist to visualize the cardiac anatomy in three dimensions. This integration helps guide the catheter to the target area and provides a comprehensive view of the ablation procedure. Figure 5A In FIG, ablation labels 501 are shown on the map and correspond to the locations of ablation sites.

[0076] In some examples, during medical procedures such as cardiac ablation, a Fast Anatomical Map (FAM) (e.g., Figure 5A and Figure 5B 5 (shown in FIG) is generated and used to provide a 3D map of heart 500. The points used to generate the FAM are collected without regard to the heart's respiration or other conditions (such as when a catheter is pushed against a tissue wall). The fact that such points are used to generate the FAM may result in the FAM being too large. In other examples, vein 502 may lack accuracy on the FAM due to missing data points. Figure 5B An electroanatomical map of the heart is depicted with ablation tags 501a attached. Ablation tags 501a pass under vein 502 and continue around the surface of the heart.

[0077] In some examples, techniques are performed to cause the FAM (which, as described above, may be oversized or inaccurate) to conform to or fit the anatomy defined by the ablation tag 501a. In some cases, this occurs when the physician is performing an ablation, the catheter is in contact with the tissue, but the ablation electrode is not visible on the surface (because the surface is oversized). In response, the technician cuts back the FAM to ensure that the ablation tag is placed on the surface and not within the surface. This process requires "fitting" the anatomy in a way that correctly places the ablation tag on the surface. During this fitting, the position information of the ablation tag 501, 501a is deemed more accurate and is therefore weighted more heavily at the location of the ablation tag than other data used to generate the FAM. Figure 5BIn the example of , anatomical fitting results in a visual artifact that causes the underside of vein 502 to appear squeezed at the location identified by arrow 505, where vein 502 meets a heart chamber. This "squeeze" artifact arises when anatomical fitting causes the portion of the heart shown on the map proximal to the ablation label to shrink without shrinking or adjusting the remainder of the FAM, and causes vein 502 to erroneously take on an appearance consistent with stenosis. As explained below, the techniques described herein provide a solution for removing this artifact from the FAM by conforming the remainder of vein 502 (not proximal to ablation label 501a) in a manner consistent with the shrinkage of vein 502 proximal to label 501a, so that vein 502 no longer appears to suffer from stenosis. The techniques described herein are not limited to the correction of stenosis-like artifacts, but are more generally applicable to the processing of FAMs that include data points of varying levels of accuracy.

[0078] Figure 6 Depicts an electroanatomical map of a heart and its median axis according to an example. Figure 5B On the contrary, Figure 6 , the ablation labels 501a on the anterior surface are shown using solid dots, while the ablation labels 501b on the posterior surface of the heart are shown using dots in outline. Also shown are the medial axis 601 of the heart 500 and the medial axis 601a of the vein 502. In some examples, the system 100 determines and displays the medial axes 601, 601a during the ablation procedure. The medial axis, sometimes referred to as the skeleton or centerline, is a geometric concept used in computational geometry and represents the set of points within a shape where there is more than one point equidistant from the boundary of the shape. The medial axis is generally considered to represent the core or central portion of a shape. For example, in medical imaging, the medial axis can be used to represent the central structure of an organ, such as the heart 500. Although in Figure 6 In the example of FIG, the entire intermediate axis 601 is shown as being determined by the system 100, but in other examples (e.g., Figure 11 ), only one or more points on the median axis are estimated. It will be understood that references herein to "estimating" a point on the median axis include selection of a previously calculated point on the median axis as well as other techniques in which one or more points along the median axis are estimated.

[0079] Still refer to Figure 6As part of the technique for removing the "squeeze" artifact, identified by arrow 505, from the map, system 100 computes at least one best-fit ellipse 602 that passes through and lies within vein 502 in a plane perpendicular to medial axis 601a. In some examples, best-fit ellipse 602 is the ellipse determined to be the most appropriate or optimal representation of a set of data points represented by ablation labels on the surface of vein 502 in the plane of the ellipse. Fitting the ellipse to these points involves finding an ellipse that minimizes some measure of difference between the ellipse and the data points on the surface of vein 502 in the plane of the ellipse. Various methods exist for fitting an ellipse to a set of points, and the techniques described herein are not limited to a particular method for determining a best-fit ellipse. A common method for determining a best-fit ellipse suitable for the techniques described herein is the least squares method, in which the sum of the squared distances between the data points on the surface of vein 502 in the plane of the ellipse is minimized. It should be understood that a best-fit circle is a special case of an ellipse in which the two foci coincide at the center, resulting in zero eccentricity. While the description set forth herein uses a best-fit ellipse to conform the FAM (and, for example, the vein 502) to the size information provided by the ablation label 501a, the use of other best-fit shapes, including a best-fit circle and a best-fit closed spline, is within the scope of this disclosure. A best-fit closed spline refers to a spline curve that has been adjusted or fitted to a set of data points in a manner that minimizes some measure of difference between the spline and the given data.

[0080] In some examples, after determining a best-fit ellipse based on the collected data points, the size of the best-fit ellipse is compared to minimum and / or maximum thresholds. In one example, these thresholds correspond to minimum and maximum vein sizes associated with typical vein sizes of a person having a profile similar to the patient's profile. In these examples, if the best-fit ellipse is less than the minimum threshold and / or greater than the maximum threshold, the best-fit ellipse calculated based on the collected data points is not used for further calculations. In some such examples, if the best-fit ellipse calculated based on the collected data points is less than the minimum value, an ellipse with a size equal to the minimum threshold is substituted; and / or if the best-fit ellipse calculated based on the collected data points is greater than the maximum value, an ellipse with a size equal to the maximum threshold is substituted.

[0081] exist Figure 6 In the embodiment of , data points corresponding to ablation labels are not available at locations other than the area closest to the rightmost best-fit ellipse 602. In this case, the system 100 may lack the data points needed to separately calculate further best-fit ellipses along the median axis. Figure 6 In an embodiment, a copy of the rightmost ellipse is projected along the median axis at an angle perpendicular thereto, rather than computing such further best-fit ellipses.

[0082] Figure 7 An electroanatomical map of a pulmonary vein 502 according to an alternative embodiment is depicted, showing its median axis 601a, wherein the system 100 calculates additional best-fit ellipses 603-605, each of which passes through and lies within the vein 502 in a plane perpendicular to the median axis 601a. In the example shown, the best-fit ellipse 602a is positioned proximate to the location of ablation tags 501a, 501b (not shown), which, as described above, corresponds more closely to the actual dimensions of the vein than other points on the FAM. The best-fit ellipses 603-605 are calculated based on available data at different cross-sections of the mapping volume of the vein 502 positioned perpendicular to the median axis 601a (e.g., corresponding to additional ablation tags of the vein 502). In one example, the major and minor axis lengths of each of the best-fit ellipses 603-605 are reduced so as to correspond to or be equal to the major and minor axis lengths, respectively, of the best-fit ellipse 602. In another embodiment, information indicating the size of the vein is derived from a pre-acquired image such as a CT or MRI and is used to adjust or shrink the ellipses 603-605. In a further embodiment, information about the size of the vein is estimated based on the size of other veins (e.g., 2-3 other veins) depicted in the electroanatomical map, and this estimate is used to adjust or shrink the ellipses 602-605. In yet another embodiment, information indicating the amount of reduction that the vein will require is estimated based on the amount of reduction required for other veins, and this estimate is used to adjust or shrink the ellipses 602-605. Although in the example shown, four best-fit ellipses are used along the length of the vein 502, any appropriate number of best-fit ellipses may be used to implement the techniques described herein. After the best-fit ellipses 603-605 are each reduced to a size that more closely corresponds to the size of the best-fit ellipse 602, the corrected volume of the vein 502 is determined by the mapping system, as explained more fully below.

[0083] Figure 8 Depicts something like Figure 6 602a, except that copies 602b-602d of the rightmost best-fit ellipse 602 are projected along the median axis at a perpendicular angle thereto. After the copies 602b-602d are projected along the median axis, the mapping system determines the corrected volume of the vein 502, as explained more fully below. Although in the example shown, four copies of the ellipse 602a are used along the length of the vein 502, any suitable number of copies may be used to implement the techniques described herein.

[0084] In combination Figures 6 to 8 After calculation of the ellipse as described in the example of , the corrected volume of the vein 502 is determined by the mapping system. Figure 9 In the example shown, system 100 calculates a new volume 901 (corresponding to the corrected surface of vein 502) by interpolating between the boundaries of copies 602a-602d of ellipse 601a along median axis 601a. For the purposes of the techniques described herein, volume 901 is considered to be a generalized cylinder or ruled surface (like a pipe or tube) extending along median axis 601a; however, because volume 901 corresponds to a vein, its shape will not correspond to a perfect or regular cylinder. After calculating volume 901, voxels in the FAM between original volume 902 and new volume 901 are removed, and an updated version of vein 502 (without the aforementioned artifacts) is displayed. While in the above example, voxels between original volume 902 and new volume 901 are removed in an automated manner in a single step (e.g., initiated by a single click by the operator via a user interface), it will be appreciated that the removal of these voxels can be performed in multiple steps using an automated reduction procedure, where voxels from volume 902 are layered and reduced until new volume 901 is reached. In some examples, this step-by-step procedure is accomplished by the operator cutting back successive layers from the original volume 902 via a user interface on the display 27 .

[0085] Although Figure 9 In the example of , the volume 901 is calculated based on four copies of a best fit ellipse, but it will be understood that in an example such as Figure 7 In other examples of the illustrated example, additional, separately calculated best-fit ellipses are used to calculate volume 901. In some examples, two or more best-fit ellipses are used. In some examples, the number of best-fit ellipses used to calculate tubular volume 901 involves a trade-off between accuracy and efficiency. In these examples, the computational time required to calculate each best-fit ellipse is balanced against the increased accuracy of volume 901 associated with each additional best-fit ellipse, and the optimal number of best-fit ellipses is selected based on these considerations.

[0086] Figure 10 Depicted according to the example Figure 5B A side-by-side comparison of a map of (left) and an updated version of that map that has been modified according to the techniques described herein (right). Figure 5B In the example of , the anatomical structure fitting results in a visual artifact that causes the underside of the vein 502 to appear squeezed at the location identified by arrow 505, where the vein 502 meets the heart chamber. Figure 10The map shown on the middle right side is such that the remaining portion of vein 502 along length 504c has been shrunk to correspond more closely in size to the portion of the vein proximate region 505. In the revised map, vein 502 appears healthy and no longer resembles a vein suffering from stenosis.

[0087] Although in the above example, the techniques for modifying FAM are described in conjunction with vein 502, the techniques described herein are not limited to veins and may be applied to other anatomical structures in the heart or elsewhere in the human body.

[0088] Figure 11 Depicted is an electroanatomical map of the heart according to another example. Figures 6 to 8 In the example of , sufficient data points are calculated to define all or most of the middle axis 601a, but Figure 11 In the example above, the entire middle axis is not calculated. Figure 11 In the example of , a limited number of data points (e.g., one or more data points) are estimated to be along the median axis. Figure 11 In the example of FIG. 5 , a best-fit ellipse 602 is calculated as the ellipse that most appropriately or optimally represents a set of data points represented by ablation labels on the surface of vein 502 in the plane of the ellipse, as shown above. System 100 calculates a center point 901 of ellipse 602 and a radius 902 of ellipse 602. In one embodiment, system 100 estimates that center point 901 is located along the medial axis (not shown) of vein 502. System 100 projects a distance corresponding to line 903 in a direction perpendicular to the plane of ellipse 602 to estimate additional data points 904 along the medial axis. System 100 identifies point 904 by projecting a distance corresponding to the length of radius 902 from point 906 along line 905. Line 905 is perpendicular to line 903. System 100 identifies point 907 on the map surface that is closest to point 906 and uses point 907 to calculate a closed curve 908 that estimates the surface of vein 502 at a cross section through point 904. In conjunction with US Pat. No. 11,461,895 owned by the assignee of the present application, for example Figure 3 The discussion of the disclosed technique for calculating the closed curve 908 is incorporated herein by reference in its entirety. Figure 11 Only a single closed curve is shown in FIG, but it should be understood that in other examples, the system 100 calculates multiple additional closed curves along the vein 502 by repeating the above process until multiple closed curves are determined along the length of the vein.

[0089] continue Figure 11For example, the system 100 calculates a new volume (corresponding to the corrected surface of the vein 502) by interpolating between the boundary of the ellipse 602 and each consecutive closed curve calculated along the vein 502. This process is similar to combining Figure 9 The process described above is different in that a closed curve is used instead of Figure 9 . The new volume corresponds to a generalized cylinder or ruled surface (like a pipe or tube) extending along the vein. After calculating the new volume, the voxels in the FAM between the original volume and the new volume are removed, and an updated version of the vein 502 is displayed. The voxels between the original volume and the new volume 901 are removed in an automated manner in a single step (e.g., actuated by a single click of the operator via a user interface), or are removed in multiple steps using an automated reduction procedure, wherein the voxels from the old volume are reduced layer by layer until the new volume is reached. In some examples, this step-by-step procedure is accomplished by the operator reducing successive layers from the original volume via a user interface on the display 27.

[0090] Now go to Figure 12 , shows a method 1200 according to one or more embodiments. The method 1200 is derived from Figure 1 Workstation 55, Figure 2 The local computing device 106, Figure 2 Remote computing system 108 and / or Figure 4 The method 1200 illustrates an example of how the system 100 generates and presents a map (e.g., one or more 3D models) of an anatomical structure on a user interface and modifies such a map according to the techniques described herein, for example, during an EP procedure (e.g., an ablation procedure).

[0091] Method 1200 begins at block 1201, where a first electroanatomical map including an anatomical structure having a mapping volume with a substantially tubular shape is displayed on a user interface. In one example, the first electroanatomical map corresponds to Figure 5B The map shown has an anatomical structure with a mapping volume having a substantially tubular shape corresponding to Figure 5B The vein 502 shown, and the user interface corresponds to the display device 27 ( Figure 1 In this example, the anatomical map depicts a 3D rendering of the heart and includes features such as one or more ablation labels.

[0092] At block 1202, at a first cross-section of a mapping volume, a first best-fit ellipse (or other best-fit shape) is determined based on data points associated with the first cross-section of the mapping volume. In one example, the first best-fit ellipse corresponds to ellipse 602 (at Figure 7 middle).

[0093] At block 1203, at least one point along the median axis (e.g., axis 601a) of the mapping volume (e.g., vein 502) is estimated. Figure 6 In the example of FIG, the entire middle axis 601 is shown as being determined (or estimated) by the system 100, but in other examples (e.g., Figure 11 It will be understood that references herein to "estimating" a point on the median axis include selection of a previously calculated (estimated) point on the median axis as well as other techniques in which one or more points along the median axis are estimated (e.g., Figure 11 technology).

[0094] In block 1204, at a second cross-section of the mapping volume, a second point along the median axis on the second cross-section is estimated. In some examples, a copy of the first best-fit ellipse is positioned at the second cross-section. In some such examples, additional copies of the first best-fit ellipse are positioned at additional cross-sections along the vein in a direction perpendicular to the estimated median axis. In other examples, a second best-fit ellipse is separately calculated and positioned at the second cross-section. In one example, the second best-fit ellipse is initially calculated based on the original volume 902 of the vein 502 and is then modified (or, for example, shrunk) to more closely correspond in size to the first best-fit ellipse. In some such examples, additional best-fit ellipses (computed separately) are positioned at additional cross-sections along the vein in a direction perpendicular to the estimated median axis. In other embodiments, a combination of copies of the first best-fit ellipse and additional separately calculated best-fit ellipses are positioned along the vein. As described above, other best-fit shapes are within the scope of the techniques described herein.

[0095] In block 1205, a generalized cylindrical volume is calculated along the estimated median axis and spanning between the first cross section and the second cross section based on the first best fit ellipse. In one example, the generalized cylindrical volume corresponds to volume 901 (in Figure 9 ), and is determined by interpolating between the boundaries of copies of the first best fit ellipse or between the first best fit ellipse and the second best fit ellipse along the estimated median axis. In some embodiments, where multiple best fit ellipses are determined along the length of the vein 502, a volume is determined in block 1205 by interpolating between the boundaries of the multiple best fit ellipses along the estimated median axis. In block 1206, data points (or in some cases, voxels) outside the volume are removed. In some examples, this step includes removing all voxels between the new volume 901 and the original volume 902, such as Figure 9In block 1207, a second electroanatomical map is displayed on a user interface (e.g., on a Figure 10 ), the second electroanatomical map having an updated version of the anatomy generated without the removed data points.

[0096] In some examples, Figure 12 The techniques in are applied to veins associated with the myocardium, and data points associated with a first cross-section of the mapping volume correspond to ablation labels. In some such examples, at one or more of a plurality of additional cross-sections of the mapping volume perpendicular to and along the length of the median axis, the data points associated with the cross-section do not correspond to ablation labels. In some examples, the first best-fit ellipse is a circle, and the substantially tubular shape is a substantially cylindrical shape. In some embodiments, the electroanatomical map is a rapid anatomical map generated during a cardiac ablation procedure.

[0097] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functions and operations of possible specific implementations of the systems, methods and computer program products according to various embodiments of the present invention. In this regard, each box in the flowchart or block diagram may represent a module, fragment or portion of an instruction that includes one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions indicated in the box may not occur in the order indicated in the accompanying drawings. For example, depending on the functions involved, two boxes shown in succession may actually be executed substantially simultaneously, or the boxes may sometimes be executed in the opposite order. It should also be noted that each box in the block diagram and / or flowchart illustration and the combination of boxes in the block diagram and / or flowchart illustration can be implemented by a dedicated hardware-based system that performs a specified function or action or by a combination of dedicated hardware and computer instructions.

[0098] Although features and elements are described above in detail, it will be appreciated by those skilled in the art that each feature or element may be used alone or in any combination with other features and elements. In addition, the methods described herein may be implemented in a computer program, software, or firmware incorporated into a computer-readable medium for execution by a computer or processor. As used herein, a computer-readable medium should not be understood as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse passing through a fiber optic cable), or an electrical signal transmitted by wire.

[0099] Examples of computer-readable media include electronic signals (transmitted via a wired or wireless connection) and computer-readable storage media. Examples of computer-readable storage media include, but are not limited to, registers, cache memory, semiconductor memory devices, magnetic media (e.g., internal hard disks and removable disks), magneto-optical media, optical media (e.g., compact disks (CDs) and digital versatile disks (DVDs)), random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), and memory sticks. A processor associated with software can be used to implement a radio frequency transceiver for use in a terminal, base station, or any host computer.

[0100] The terms used herein are for the purpose of describing specific embodiments only and are not intended to be limiting. As used herein, unless the context clearly indicates otherwise, the singular forms "a," "an," and "the" include plural references. It should also be understood that the terms "comprises" and / or "comprising," when used in this specification, specify the presence of the features, integers, steps, operations, elements, and / or parts, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, parts, and / or groups thereof.

[0101] The descriptions of various embodiments herein are presented for illustrative purposes and are not intended to be exhaustive or limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is selected to best explain the principles of the embodiments, practical applications or technical improvements over existing technologies on the market, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A method for correcting an electroanatomical map generated using a catheter positioned in a human body, the catheter having a plurality of electrodes, wherein: The map is generated from data points acquired using the electrodes as the catheter moves within the body during a medical procedure, the method comprising: displaying a first electroanatomical map including an anatomical structure having a mapping volume with a substantially tubular shape; determining, at a first cross-section of the mapping volume, a first best-fit ellipse based on data points associated with the first cross-section of the mapping volume; estimating a first point along a medial axis of the mapping volume based on the center of the first best-fit ellipse; estimating a second point along the medial axis at a second cross-section of the mapping volume; the first cross-section being different from the second cross-section; calculating a generalized cylindrical volume spanning between the first cross-section and the second cross-section based on at least the first best-fit ellipse; removing data points outside the generalized cylindrical volume from the mapping volume; and A second electroanatomical map is displayed having an updated version of the anatomical structure generated without the removed data points. 2 . The method of claim 1 , further comprising determining a plurality of points defining the median axis, wherein the first cross-section is perpendicular to the median axis and the step of estimating the second point comprises selecting one of the plurality of points.

3. The method according to claim 1, wherein The anatomical structure is a vein associated with the myocardium.

4. The method according to claim 1, wherein The data points associated with the first cross-section of the mapping volume correspond to ablation labels.

5. The method according to claim 4, further comprising: estimating additional points along the median axis at additional cross-sections of the mapping volume; and wherein the generalized cylindrical volume spans the first cross-section, the second cross-section, and the further cross-section.

6. The method according to claim 4, wherein: Data points associated with each of the second cross-section and the further cross-section of the mapping volume do not correspond to ablation labels.

7. The method according to claim 6, wherein: The generalized cylindrical volume is a substantially cylindrical shape.

8. The method according to claim 1, wherein The electroanatomical map is a rapid anatomical map.

9. A system for correcting an electroanatomical map generated using a catheter positioned in a human body, the catheter having a plurality of electrodes, wherein: The map is generated from data points acquired using the electrodes as the catheter moves within the body during a medical procedure, the system comprising: a memory storing the electroanatomical map; a processor coupled to the memory; and a user interface coupled to the processor; The processor is configured to perform the following operations: displaying on the user interface a first electroanatomical map including an anatomical structure having a mapping volume with a substantially tubular shape; determining, at a first cross-section of the mapping volume, a first best-fit ellipse based on data points associated with the first cross-section of the mapping volume; estimating a first point along a medial axis of the mapping volume based on the center of the first best-fit ellipse; estimating a second point along the medial axis at a second cross-section of the mapping volume; the first cross-section being different from the second cross-section; calculating a generalized cylindrical volume spanning between the first cross-section and the second cross-section based on at least the first best-fit ellipse; removing data points outside the generalized cylindrical volume from the mapping volume; and A second electroanatomical map having an updated version of the anatomical structure generated without the removed data points is displayed on the user interface.

10. The system of claim 9, further comprising determining a plurality of points defining the intermediate axis, wherein The first cross-section is perpendicular to the median axis and the step of estimating the second point includes selecting one of the plurality of points.

11. The system according to claim 9, wherein: The anatomical structure is a vein associated with the myocardium.

12. The system according to claim 10, wherein: The data points associated with the first cross-section of the mapping volume correspond to ablation labels.

13. The system according to claim 12, wherein: The processor is further configured to: estimating additional points along the median axis at additional cross-sections of the mapping volume; and wherein the generalized cylindrical volume spans the first cross-section, the second cross-section, and the further cross-section.

14. The system according to claim 12, wherein: The data points associated with the second cross-section and each additional cross-section of the mapping volume do not correspond to ablation labels.

15. The system according to claim 14, wherein: The generalized cylindrical volume is a substantially cylindrical shape.

16. The system according to claim 10, wherein: The electroanatomical map is a rapid anatomical map.

17. A non-transitory computer-readable medium storing instructions, When executed by a processor, the instructions cause the processor to perform operations including: displaying a first electroanatomical map including an anatomical structure having a mapping volume with a substantially tubular shape; determining, at a first cross-section of the mapping volume, a first best-fit ellipse based on data points associated with the first cross-section of the mapping volume; estimating a first point along a medial axis of the mapping volume based on the center of the first best-fit ellipse; estimating a second data point along the medial axis at a second cross-section of the mapping volume; the first cross-section is different from the second cross-section; calculating a generalized cylindrical volume along the median axis and spanning between the first cross-section and the second cross-section based on at least the first best-fit ellipse; removing data points outside the generalized cylindrical volume from the mapping volume; as well as A second electroanatomical map is displayed having an updated version of the anatomical structure generated without the removed data points.

18. The non-transitory computer readable medium of claim 18, wherein: The operations also include determining a plurality of points defining the median axis, wherein the first cross-section is perpendicular to the median axis and estimating the second point includes selecting one of the plurality of points.

19. The non-transitory computer readable medium of claim 17, wherein: The anatomical structure is a vein associated with the myocardium.

20. The non-transitory computer readable medium of claim 19, wherein: The data points associated with the first cross-section of the mapping volume correspond to ablation labels.

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