Multilayer visualization of data points on a heart map

Abstract

To provide methods and systems for multi-layered visualization of data points over a heart map.SOLUTION: A system includes a display and a processor. The processor is configured to (i) receive a dataset including multiple data points, each data point corresponding to one or more properties of an organ of a patient, (ii) produce, based on a clustering criterion, at least a cluster including two or more of the data points, and (iii) produce, and present on the display, a map of the organ and at least an object indicative of the cluster. In response to selection of the object by a user, the processor is configured to produce, and present on the display, a two-dimensional (2D) table including the one or more properties of each of the clustered data points.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention generally relates to medical devices, and more particularly to a method and system for multi-layer visualization of data points on a cardiac map.

Background Art

[0002] Various techniques have been disclosed for visualizing information such as electrophysiological data on anatomical maps.

[0003] For example, U.S. Patent Application Publication No. 2018 / 0279896 describes a system for analyzing electrophysiological data, particularly intracardiac electrogram data. The system includes a data processing and control unit for processing electrophysiological data, and a data output unit includes a data output screen for displaying the results of electrophysiological data analysis. The data processing and control unit is configured to receive electrophysiological data obtained from a mapping catheter assembly including an electrode assembly having a plurality of n electrodes, and each electrode is configured to measure electrophysiological data in the form of an electrogram signal. The data processing and control unit includes an engine for performing optical flow analysis of the electrophysiological data to generate a series of vector data representing the average movement speed and movement direction of clusters of electrophysiological data. The data output unit is configured to display the vector data on the data output screen of the data output unit.

[0004] U.S. Patent No. 10,709,347 describes a system for displaying cardiac graphic information related to the cause and location of cardiac disease to assist in the assessment of cardiac disease. The cardiac graphic display system provides intra-cardiogram similarity ("ICS") graphics and source location ("SL") graphics. The ICS graphics include a grid with x and y axes representing patient cycles of the patient's electrocardiogram, where the intersection of patient cycle identifiers indicates similarity between patient cycles. The SL graphics provide a depiction of the heart with the indicated source location. The source location is identified based on the similarity of the patient cycle to library cycles of library electrocardiograms in a library of electrocardiograms. [Overview of the Initiative] [Means for solving the problem]

[0005] Embodiments of the present invention described below provide a system comprising a display and a processor. The processor is configured to (i) receive a dataset containing a plurality of data points, each data point corresponding to one or more characteristics of a patient's organs; (ii) generate at least one cluster containing two or more of the data points based on clustering criteria; and (iii) generate at least one object representing the organ map and clusters and present it on the display. In response to the user's selection of an object, the processor is configured to generate a two-dimensional (2D) table containing one or more characteristics of each of the clustered data points and present it on the display.

[0006] In some embodiments, the organ includes the patient's heart, and the clustering criteria are selected from a list of criteria consisting of (i) the location of the data point in the heart, (ii) the form of the signal acquired at the data point, (iii) the local activation time (LAT) measured at the data point, and (iv) anatomical features at the data point. In other embodiments, the processor is configured to present at least objects by displaying them on a map.

[0007] In one embodiment, the processor is configured to present at least the objects by generating them and displaying them in an additional 2D table. In another embodiment, the processor is configured to assign representative data values ​​to clusters that represent the computed values ​​corresponding to clustered data points.

[0008] Furthermore, according to one embodiment of the present invention, a method is provided which includes receiving a dataset containing a plurality of data points, each data point corresponding to one or more characteristics of a patient's organs. At least one cluster containing two or more of the data points is generated based on clustering criteria. At least one object representing the organ map and clusters is generated and presented, and in response to the user's selection of the object, a two-dimensional (2D) table containing one or more characteristics of each of the clustered data points is generated and displayed.

[0009] According to one embodiment of the present invention, a method for multilayer visualization is further provided, which includes receiving a dataset containing a plurality of data points, each data point corresponding to one or more characteristics of a patient's organs. A first visualization layer is generated by clustering at least one cluster containing two or more of the data points based on a clustering criterion, and objects representing the clusters are displayed. A second visualization layer is generated, which includes a two-dimensional (2D) table having one or more characteristics of each of the clustered data points, and the 2D table is displayed in response to object selection by the user.

[0010] In some embodiments, generating the first visualization layer includes displaying objects on a map. In other embodiments, generating the first visualization layer includes displaying objects in an additional 2D table. In yet another embodiment, generating the first visualization layer includes assigning representative data values ​​to objects that represent calculated values ​​corresponding to clustered data points. [Brief explanation of the drawing]

[0011] This invention will be more fully understood by considering the following "Modes for Carrying Out the Invention" in conjunction with the drawings. [Figure 1] This is a schematic diagram of a catheter-based tracking and ablation system according to an exemplary embodiment of the present invention. [Figure 2] This is a schematic diagram of a multilayer visualization of data points presented in a two-dimensional table of clusters and selected clusters, according to an exemplary embodiment of the present invention. [Figure 3] This flowchart schematically illustrates a method for visualizing data points on a heart map according to an exemplary embodiment of the present invention. [Figure 4] This flowchart schematically illustrates a method for visualizing data points on a heart map according to an exemplary embodiment of the present invention. [Modes for carrying out the invention]

[0012] Overview Some medical procedures, such as radiofrequency (RF) ablation, require electroanatomical mapping of the heart before the ablation is performed. During mapping, the physician inserts a catheter with multiple sensing electrodes, each electrode configured to generate one or more signals that indicate electrophysiological (EP) signals sensed in the patient's heart tissue.

[0013] The signals generated by the catheter's sensing electrodes can contain thousands of data points, for example, over 50,000. Based on these data points, physicians can determine a plan for ablating tissue within the heart. However, a large number of data points can sometimes overwhelm physicians and hinder the development of an ablation plan.

[0014] The embodiments of the present invention described below provide an improved technique for presenting a large number (e.g., hundreds or thousands) of data points that represent one or more characteristics of a patient's organ, such as the patient's heart.

[0015] In some embodiments, the system for presenting data points comprises a display and a processor. The processor is configured to receive a dataset containing multiple data points, each data point corresponding to one or more characteristics of the patient's heart.

[0016] In some embodiments, the processor is configured to generate at least one cluster (and typically multiple clusters) containing multiple data points based on one or more clustering criteria. The processor is further configured to generate and present on a display multiple objects representing an anatomical map of the heart and multiple clusters.

[0017] In principle, clustering data points simplifies their visualization on an anatomical map, which can therefore help physicians determine ablation plans. However, in some cases, clustering may conceal or ignore one or more data points that have characteristic values ​​that could influence the ablation plan.

[0018] In some embodiments, the processor is configured to assign a representative data value to each cluster, representing the calculated value corresponding to the clustered data points. For example, the mean and standard deviation of the values ​​of a selected characteristic for the ablation criterion are calculated for all data points clustered into their respective clusters. In some embodiments, the physician can view the data values ​​by hovering the system's trackball or mouse over the clusters displayed on an anatomical map of the heart. Additionally or alternatively, the physician may use any other suitable technique, such as viewing the data values ​​for each cluster in a table containing some or all of the clusters.

[0019] In some embodiments, the processor is configured to analyze the data values ​​of a cluster and provide a warning to the physician if one or more of the data values ​​exceed a predefined threshold.

[0020] In some cases, the data values ​​(or number of values) of a given cluster can attract a physician's attention. For example, if the standard deviation is greater than a predefined threshold. In such cases, the physician can select the given cluster by, for example, clicking on an object representing the given cluster displayed on an anatomical map.

[0021] In some embodiments, in response to the selection of an object by a physician (or any other user of the system), the processor is configured to generate a two-dimensional (2D) table that includes the respective characteristics of the data points clustered into a given cluster and present it on a display.

[0022] The disclosed technology provides a physician with a multi-layer visualization of data points indicative of the characteristics of a patient's organ. The processor is configured to generate a first visualization layer by clustering at least one cluster that includes two or more of the data points based on clustering criteria and display an object indicative of the cluster on an anatomical map. The processor is further configured to generate a 2D table having one or more characteristics of each of the clustered data points. Further, in response to the selection of an object by a user (e.g., a physician), the processor is configured to display the 2D table on a display (i.e., the 2D table constitutes a second visualization layer), such that as a result, the physician can overview the characteristics of one or more data points clustered within a given cluster.

[0023] The disclosed technology can be useful for a physician to collect and analyze diagnostic data for determining various types of treatment procedures, such as but not limited to cardiac RF ablation. Specifically, by providing the physician with a multi-layer visualization and display of characteristics associated with a target organ, the disclosed technology simplifies diagnosis and planning, but provides the user (e.g., a physician) with the ability to overview one or more specific data points, which can be essential for making an appropriate decision regarding a treatment plan.

[0024] Description of the System FIG. 1 is a schematic drawing of a catheter-based tracking and ablation system 20 according to an embodiment of the present invention.

[0025] In some embodiments, the system 20 comprises a catheter 22, which in this example is a cardiac catheter, and a control console 24. In embodiments described herein, the catheter 22 may be used for any preferred therapeutic and / or diagnostic purposes, such as tissue ablation within the heart 26.

[0026] In some embodiments, the console 24 includes a processor 41, which is typically a general-purpose computer, having a front-end circuit and an interface circuit 38, which is suitable for receiving signals via the catheter 22 and for controlling other components of the system 20 described herein. The console 24 further includes a user display 35 configured to receive and display a map 27 of the heart 26 from the processor 41.

[0027] In some embodiments, map 27 may include any suitable type of anatomical map generated using any suitable technique. For example, the anatomical map may be generated using anatomical images generated by using a suitable medical imaging system, or using fast anatomical mapping (FAM) technique using the CARTO® system manufactured by BiosenseWebster Inc. (Irvine, Calif.), or using any other suitable technique, or any suitable combination of the above.

[0028] Refer to inset 23 here. In some embodiments, before performing the ablation procedure, physician 30 inserts a catheter 22 through the vascular system of patient 28 lying on a table 29 to perform electroanatomical mapping of the target tissue of the heart 26.

[0029] In some embodiments, the catheter 22 includes a distal end assembly 40 having a plurality of sensing electrodes (not shown). For example, the distal end assembly 40 may include (i) a basket catheter having a plurality of splines, each spline having a plurality of sensing electrodes, or (ii) a balloon catheter having a plurality of sensing electrodes disposed on the surface of a balloon. Each sensing electrode is configured to generate one or more signals indicating the sensed electrophysiological (EP) signal in the tissue of the heart 26 in response to sensing an electrophysiological (EP) signal.

[0030] In some embodiments, the proximal end of the catheter 22 is connected, among other things, to an interface circuit 38 to transfer these signals to a processor 41 in order to perform electroanatomical mapping.

[0031] In some embodiments, during electroanatomical mapping, the signals generated by the sensing electrodes of the distal end assembly 40 may include thousands of data points, e.g., more than 50,000 data points. Based on the data points, the physician 30 determines one or more sites within the heart 26 to ablate. However, it may be difficult for the physician 30 to survey and analyze the aforementioned large number of data points, which may prolong the duration of the ablation procedure. Furthermore, the large number of data points may overwhelm the physician 30, which may degrade the quality of the ablation plan.

[0032] In the context of this disclosure and in the claims, the terms “about” or “approximately” used with respect to any number or range of numbers indicate a reasonable tolerance of dimensions that enables a part or set of components to function in accordance with the intended purpose set forth herein.

[0033] In some embodiments, the processor 41 is configured to present data points in two visualization layers, for example, on a display 35, by (i) clustering the data points based on one or more clustering criteria and displaying an object representing each cluster, and (ii) displaying a two-dimensional (2D) table containing the characteristics of each clustered data point in response to an object selection by the physician 30 (or any other user of the system 20).

[0034] In some embodiments, displaying with two visualization layers allows (i) to simplify the presentation of thousands of data points to the physician 30 by displaying data points within clusters (e.g., on top of map 27), and (ii) for the physician 30 to examine specific data points within each selected cluster. Techniques for displaying with two visualization layers are detailed in Figure 2 below.

[0035] In some embodiments, the physician 30 may use the processor 41 to cluster the data points into multiple clusters, thereby allowing the physician 30 to overview and analyze clusters consisting of smaller amounts of data. However, some of the clustered data points may be essential for making appropriate decisions regarding the ablation plan. Therefore, presenting the data points within clusters may not be sufficient to create the most clinically appropriate ablation plan.

[0036] In some embodiments, the processor 41 is configured to present data points in two or more hierarchical levels so as to (i) reduce the amount of data (e.g., by clustering) in order to simplify data analysis, and still (ii) provide the physician 30 with the ability to overview one or more specific data points (e.g., within a cluster).

[0037] In some embodiments, the processor 41 is configured to receive a dataset containing multiple data points, each data point corresponding to one or more characteristics of the heart 26. The processor 41 is configured to generate multiple clusters based on clustering criteria, so that at least one of the clusters contains two or more (typically tens or hundreds) data points. The processor 41 is further configured to assign a representative data value to each cluster that represents a computed value corresponding to the clustered data points.

[0038] In some embodiments, the processor 41 is configured to generate a map 27 of the heart 26 containing one or more clusters and to display objects indicating the corresponding clusters on the map 27 displayed on the display 35. Additionally or alternatively, the processor 41 is configured to display the clusters in a two-dimensional (2D) table, for example, adjacent to the anatomical map. Clustering reduces the amount of data points that will be analyzed by the physician 30, as described above.

[0039] In some embodiments, the physician 30 can select a cluster to get an overview of one or more characteristics associated with a particular data point within the cluster. In such embodiments, in response to the selection of an object representing each corresponding cluster, the processor 41 is configured to generate a 2D table containing one or more characteristics of each of the clustered data points and to display the 2D table on the display 35. These techniques are illustrated in detail in Figures 2 and 3 below.

[0040] In other embodiments, the catheter 22 may include one or more ablation electrodes (not shown) connected to a distal end assembly 40. The ablation electrodes are configured to ablate tissue at a target location in the heart 26. After determining the ablation plan, the physician 30 navigates the distal end assembly 40 to a location very close to the target location in the heart 26 by using a manipulator 32 to operate the catheter 22. Additionally or alternatively, the physician 30 may use any different type of suitable catheter for ablating tissue in the heart 26 to perform the ablation plan described above.

[0041] In some embodiments, the position of the distal end assembly 40 within the cardiac chamber is measured using a position sensor (not shown) of a magnetic position tracking system. In this embodiment, the console 24 includes a drive circuit 34, which is configured to drive a magnetic field generator 36 located at a known position outside the body of a patient 28 lying on a table 29, for example, under the patient's torso. The position sensor is connected to the distal end and is configured to generate a position signal in response to an external magnetic field sensed from the magnetic field generator 36. The position signal indicates the position of the distal end of the catheter 22 in the coordinate system of the position tracking system.

[0042] This position sensing method has been implemented in various medical applications, for example, in the CARTO® system manufactured by Biosense Webster Inc. (Irvine, Calif.), and is detailed in U.S. Patents 5,391,199, 6,690,963, 6,484,118, 6,239,724, 6,618,612 and 6,332,089, PCT International Publication 96 / 05768, and U.S. Patent Publications 2002 / 0065455(A1), 2003 / 0120150(A1) and 2004 / 0068178(A1), all of which are incorporated herein by reference.

[0043] In some embodiments, the coordinate system of the position tracking system is aligned with the coordinate systems of system 20 and map 27, and as a result, the processor 41 is configured to display the position of the distal end of the catheter 22 on map 27.

[0044] In some embodiments, the processor 41 typically includes a general-purpose computer, which is programmed with software to perform the functions described herein. The software can be downloaded to the computer in electronic form, for example, over a network, or alternatively or additionally, it can be provided and / or stored on a non-temporary physical medium such as magnetic memory, optical memory, or electronic memory.

[0045] This particular configuration of System 20 is shown as an example to illustrate the specific problems addressed by embodiments of the present invention and to demonstrate the application of these embodiments in improving the performance of such systems. However, embodiments of the present invention are by no means limited to this particular type of exemplary system, and the principles described herein may also be applied to other types of medical systems.

[0046] Two-tiered visualization of data points on a heart map Figure 2 is a schematic diagram of a multi-layer visualization of a map 27 and data points 55 displayed on a display 35 according to one embodiment of the present invention.

[0047] In some embodiments, the processor 41 is configured to receive the signal described in Figure 1 above from the distal end assembly 40. The signal includes a dataset containing a plurality of data points 55. Each data point corresponds to one or more characteristics of the heart 26. The processor 41 is configured to generate a plurality of clusters based on clustering criteria, at least one of which contains two or more (typically tens, hundreds, or thousands) of data points 55. In this embodiment, the processor 41 is configured to generate clusters 66 and 68, and optionally, (unclustered) data points 55, and present them on a map 27 displayed on the display 35.

[0048] In some embodiments, the processor 41 is configured to present clusters 66, 68, and 70, as well as data points 55, on the display 35 using any preferred objects. In this embodiment, data points 55 may be presented using circular objects having a given color (e.g., orange) and a given diameter; one or more clusters 66 may be presented using yellow circular objects having one or more different diameters; one or more clusters 68 may be presented using red circular objects having one or more different diameters; and cluster 70 may be presented using green circular objects having one or more different diameters.

[0049] In other embodiments, the object representing the cluster may have any preferred shape other than circular, such as an ellipse or any kind of irregular shape.

[0050] In some embodiments, the processor 41 is configured to assign a diameter to a circular object that indicates the number of clustered data points 55. In other embodiments, the diameter of the circular object may indicate the area covered by the clustered data points 55. In this embodiment, objects representing clusters 66 and 68 typically have a larger diameter than objects representing cluster 70. Similarly, objects representing cluster 70 have a larger diameter than objects representing data points 55.

[0051] In some embodiments, the processor 41 is configured to apply multiple different clustering criteria to cluster data points 55 in different sections of the map 27 and to assign different colors or shapes to present all characteristics and / or clustering criteria on the map 27.

[0052] In some embodiments, the clustering criteria may be based on one or more characteristics of the heart 26, or on characteristics of any other organ to be targeted. In this embodiment, the processor 41 is configured to select a clustering criterion from a list of criteria consisting of (i) the location of data point 55 on map 27 of the heart 26, (ii) the form of the EP signal acquired by the electrodes of the distal end assembly 40 at the location of data point 55, (iii) local activation time (LAT) measured by the electrodes of the distal end assembly 40 at the location of data point 55, (iv) anatomical features of the heart 26 at each data point 55, or any other preferred characteristics and / or clustering criteria.

[0053] In some embodiments, the processor 41 is further configured to assign a representative data value to each cluster that represents the calculated value corresponding to the clustered data points 55. For example, the console 24 may include an input device such as a trackball or mouse, and when the physician 30 hovers the input device over a cluster 66, the processor 41 is configured to display on the display 35 the calculated value corresponding to the respective cluster 66.

[0054] In some embodiments, the calculated values ​​may include, for example, the mean and standard deviation of parameters selected for clustering criteria, which are calculated by the processor 41 for the clustered data points 55 of the selected cluster 66. Additionally or alternatively, the calculated values ​​may include any other statistical calculations and / or other properties, such as the minimum, maximum, or average distance between adjacent clustered data points 55 of the selected cluster 66.

[0055] In other embodiments, instead of, or in addition to, the objects displayed on the map 27, the processor 41 is configured to use a two-dimensional (2D) table (not shown), also referred to herein as the “cluster table” or “additional table,” to present at least some of the clusters 66, 68, and 70, and / or at least some of the data points 55. In such embodiments, each row of the table constitutes an object representing the corresponding cluster. The rows of the table may include, in the columns of the 2D table, some or all of the calculated values ​​of the target cluster using the techniques and embodiments described above for the circular objects displayed on the map 27.

[0056] In some cases, the physician 30 may want to survey one or more data points 55 of a given cluster. For example, if the standard deviation of LAT in one cluster 66 is greater than a predefined threshold.

[0057] In some embodiments, the processor 41 is configured to present a 2D table 77 of the selected clusters, so that the physician 30 can get an overview of the characteristics associated with each data point 55 of the corresponding clusters. In the example in Figure 2, the physician 30 (or any other user) can select an object representing a cluster 66 by, for example, clicking on an object presented on the map 27.

[0058] In some embodiments, in response to object selection by physician 30, the processor 41 is configured to generate a table 77 containing all selected (e.g., measured and / or calculated) characteristics of each data point 55 clustered into the selected cluster 66, and present it on the display 35.

[0059] In some embodiments, table 77 may include the shape and color of the object assigned to each data point 55 in table 55. In this embodiment, it is a yellow circular shape, and each data point may have a gradient representing the value of a characteristic selected for clustering, or any other selected characteristic. In response to user selection, the processor 41 is configured to allow the user to browse, read, filter, sort, or manipulate the characteristics of the data points 55 displayed in table 77.

[0060] In some embodiments, in response to a command from a user (e.g., a physician 30), the processor 41 is configured to remove table 77 from the display 35, or alternatively, to display multiple tables 77, each of which displays different clusters selected from among clusters 66, 68, and 70, as well as selected data points 55 that are not clustered.

[0061] In other embodiments, the processor 41 is configured to display a table 77 in response to the selection of the aforementioned cluster 66 from a cluster table having at least some of the clusters, as described above.

[0062] The particular presentation of Map 27, clusters, data points 55, and Table 77 in Figure 2 is shown as an example to illustrate the specific problems addressed by embodiments of the present invention and to demonstrate the applicability of these embodiments in enhancing the performance of System 20 and improving the quality and cycle time of data analysis and ablation planning. However, embodiments of the present invention are not limited to this particular type of exemplary presentation, and the principles described herein may also be applied to other types of user interfaces that are applicable to any other suitable medical procedure performed using any suitable medical system.

[0063] Figure 3 is a schematic flowchart illustrating a method for two-tiered visualization of data points 55 on a map 27 according to one embodiment of the present invention. In the context of this disclosure and the claims, the terms “two-tiered,” “multi-tiered,” “two layers,” and “multi-layered” are used interchangeably and refer to presenting any type of data in multiple layers by providing the user with the ability to select the layer or hierarchy of information they wish to visualize.

[0064] The method begins in a dataset reception step 100 using a processor 41 or any other device that receives a dataset containing multiple data points 55 from a distal end assembly 40. Each data point corresponds to one or more characteristics of the heart 26. In a cluster generation step 102, the processor 41 is configured to generate at least one cluster 66 containing two or more of the data points 55 based on a clustering criterion (or multiple clustering criteria). As shown in the example in Figure 2, the processor 41 is configured to generate multiple clusters 66, 68, and 70, each of which has multiple (e.g., hundreds or thousands) of data points 55.

[0065] In the representative data value assignment step 104, the processor 41 is configured to assign a representative data value to a cluster (e.g., cluster 66) that represents the calculated value corresponding to the data point 55 clustered within cluster 66, as detailed in Figure 2 above.

[0066] In the map and cluster presentation step 106, the processor 41 is configured to generate and present a map 27 of the heart 26 and one or more objects representing one or more clusters, such as clusters 66, 68, and 70, as detailed in Figure 2 above.

[0067] In the table presentation step 108 that completes this method, in response to the selection (by the physician 30 or any other user) of one or more of the aforementioned objects, for example, an object representing one cluster 66, the processor 41 is configured to generate and present (for example, on the display 35) a two-dimensional (2D) table 77 containing the characteristics of the data points 55 clustered in the selected cluster 66.

[0068] As detailed in Figure 2 above, in step 106, the objects representing the clustered data points may be displayed on display 35 using any other preferred presentation, for example, in an additional 2D table.

[0069] Figure 4 is a flowchart illustrating a method for two-tiered visualization of thousands of data points 55 according to another embodiment of the present invention.

[0070] In this method, the data set reception step 200 is initiated using a processor 41 that receives a data set containing multiple data points 55 from the distal end assembly 40, where each data point corresponds to one or more characteristics of the heart 26.

[0071] In the first visualization layer generation step 202, the processor 41 is configured to generate the first visualization layer by clustering at least cluster 66 (and typically additional clusters such as clusters 68 and 70) containing two or more of the data points 55, based on clustering criteria. The processor is further configured to display one or more objects that each represent one or more clusters (e.g., clusters 66, 68, and 70), as shown and detailed in Figure 2 above.

[0072] In some embodiments, the processor 41 is further configured to assign representative data values ​​to clusters (e.g., cluster 66) that represent the calculated values ​​corresponding to the data points 55 clustered within cluster 66, as also detailed in step 104 of Figures 2 and 3 above. Furthermore, in addition to, or instead of, the visible objects presented on the map 27, the processor 41 is configured to present one or more of clusters 66, 68, and 70, and optionally at least some of the data points 55, to an additional table also referred to as the cluster table described in Figure 2 above.

[0073] In the second visualization layer generation step 204 that completes the method, the processor 41 is configured to generate a second visualization layer. In this embodiment, the second visualization layer includes a 2D table 77 (shown in Figure 2 above) having the characteristics of each of the clustered data points 55. In some embodiments, as detailed in Figure 2 above, the processor 41 is configured to display the table 77 on the display 35 in response to a selection of objects representing clusters 66 by the physician 30 (or any other user).

[0074] While the embodiments described herein primarily address the visualization of electrophysiological (EP) data points on a cardiac anatomical map, the methods and systems described herein can also be used for other applications, such as mapping and visualization of any characteristics of any organ in a patient. Furthermore, the embodiments described herein can be used when presenting any kind of large amount of data (e.g., thousands or millions), such that the data is clustered using one or more clustering criteria, each cluster features annotations, and the data within each cluster can be presented using any preferred format.

[0075] Accordingly, it will be understood that the embodiments described above are cited as examples and that the present invention is not limited to those specifically shown and described above. Rather, the scope of the present invention includes both combinations and partial combinations of the various features described in the above specification, as well as variations and modifications thereof not disclosed in the prior art, which would be conceivable to those skilled in the art by reading the foregoing description. Documents incorporated into this patent application by reference shall be considered integral parts of this application, except that, in such incorporated documents, only the definitions herein shall be considered to the extent that any term is defined in a manner that contradicts the definitions expressed or implied herein.

[0076] [Implementation Method] (1) A system, The display and A processor configured to (i) receive a dataset containing multiple data points, each data point corresponding to one or more characteristics of a patient's organs; (ii) generate at least one cluster containing two or more of the data points based on clustering criteria; and (iii) generate at least one object representing the map of the organs and the clusters, and present them on the display. A system comprising a processor configured to generate a two-dimensional (2D) table containing the one or more characteristics of each of the clustered data points in response to a user's selection of the object, and to present it on the display. (2) The system according to Embodiment 1, wherein the organ includes the patient's heart, and the clustering criterion is selected from a list of criteria consisting of (i) the location of the data point in the heart, (ii) the form of the signal acquired at the data point, (iii) the local activation time (LAT) measured at the data point, and (iv) anatomical features at the data point. (3) The system according to Embodiment 1, wherein the processor is configured to present at least the objects by displaying them on the map. (4) The system according to Embodiment 1, wherein the processor is configured to generate at least the object and present the object by displaying the object in an additional 2D table. (5) The system according to Embodiment 1, wherein the processor is configured to assign representative data values ​​representing the calculated values ​​corresponding to the clustered data points to the clusters.

[0077] (6) A method, Receiving a dataset containing multiple data points, where each data point corresponds to one or more characteristics of a patient's organs, Based on the clustering criteria, generate at least one cluster containing two or more of the aforementioned data points, To generate and present at least one object representing the map of the organs and the clusters, A method comprising generating and displaying a two-dimensional (2D) table containing the one or more characteristics of each of the clustered data points in response to a user's selection of the object. (7) The method according to Embodiment 6, wherein the organ includes the patient's heart, and the clustering criterion is selected from a list of criteria consisting of (i) the location of the data point in the heart, (ii) the form of the signal acquired at the data point, (iii) the local activation time (LAT) measured at the data point, and (iv) the anatomical features at the data point. (8) The method of Embodiment 6, wherein presenting the object includes displaying the object on the map. (9) The method of Embodiment 6, wherein presenting the object includes displaying the object in an additional 2D table. (10) The method according to Embodiment 6, comprising assigning a representative data value representing a calculated value corresponding to the clustered data point to the cluster.

[0078] (11) A method for multilayer visualization, wherein the method is Receiving a dataset containing multiple data points, where each data point corresponds to one or more characteristics of a patient's organs, Based on clustering criteria, a first visualization layer is generated by clustering at least one cluster containing two or more of the data points, and an object representing the cluster is displayed. A method comprising generating a second visualization layer including a two-dimensional (2D) table having one or more of the characteristics of each of the clustered data points, and displaying the 2D table in response to the user's selection of the objects. (12) The method according to Embodiment 11, wherein generating the first visualization layer includes displaying the objects on the map. (13) The method according to Embodiment 11, wherein generating the first visualization layer includes displaying the objects in an additional 2D table. (14) The method according to Embodiment 11, wherein generating the first visualization layer includes assigning representative data values ​​to the objects that represent the calculated values ​​corresponding to the clustered data points.

Claims

1. It is a system, The display and A processor configured to (i) receive a dataset containing a plurality of data points, each data point corresponding to one or more characteristics of a patient's heart; (ii) generate at least one cluster containing two or more of the data points based on a clustering criterion; and (iii) generate at least one object representing the map of the heart and the clusters, and present them on the display. A system comprising: a processor configured to generate a two-dimensional (2D) table containing one or more of the characteristics of each of the clustered data points in response to a user's selection of the object, and to present it on the display.

2. The system according to claim 1, wherein the clustering criterion is selected from a list of criteria consisting of (i) the location of the data point in the heart, (ii) the form of the signal acquired at the data point, (iii) the local activation time (LAT) measured at the data point, and (iv) the anatomical features at the data point.

3. The system according to claim 1, wherein the processor is configured to present at least the object by displaying the object on the map.

4. The system according to claim 1, wherein the processor is configured to generate at least the objects and to present at least the objects by displaying the objects in an additional 2D table.

5. The system according to claim 1, wherein the processor is configured to assign representative data values ​​representing calculated values ​​corresponding to the clustered data points to the clusters.

6. It is a method, Receiving a dataset containing multiple data points, where each data point corresponds to one or more characteristics of the patient's heart, Based on the clustering criteria, generate at least one cluster containing two or more of the aforementioned data points, To generate and present at least one object representing the map of the heart and the cluster, A method comprising generating and displaying a two-dimensional (2D) table containing one or more of the characteristics of each of the clustered data points in response to a user's selection of the object.

7. The method according to claim 6, wherein the clustering criterion is selected from a list of criteria consisting of (i) the location of the data point in the heart, (ii) the form of the signal acquired at the data point, (iii) the local activation time (LAT) measured at the data point, and (iv) the anatomical features at the data point.

8. The method according to claim 6, wherein presenting the object includes displaying the object on the map.

9. The method according to claim 6, wherein presenting the object includes displaying the object in an additional 2D table.

10. The method according to claim 6, comprising assigning a representative data value representing a calculated value corresponding to the clustered data point to the cluster.

11. A method for multilayer visualization, wherein the method is Receiving a dataset containing multiple data points, where each data point corresponds to one or more characteristics of the patient's heart, Based on clustering criteria, a first visualization layer is generated by clustering at least one cluster containing two or more of the data points, and an object representing the cluster is displayed. A method comprising generating a second visualization layer including a two-dimensional (2D) table having one or more of the characteristics of each of the clustered data points, and displaying the 2D table in response to the user's selection of the objects.

12. The method according to claim 11, wherein generating the first visualization layer includes displaying the object on top of the map of the heart.

13. The method according to claim 11, wherein generating the first visualization layer includes displaying the objects in an additional 2D table.

14. The method according to claim 11, wherein generating the first visualization layer includes assigning representative data values ​​to the objects that represent calculated values ​​corresponding to the clustered data points.

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