Automatic demarcation of anatomical structure boundaries

Abstract

To improve demarcation of boundary of an anatomical structure for visualization.SOLUTION: A method, an apparatus, a system and a program for automatically demarcating a boundary of segments of an anatomical structure include: providing a processor having a memory; receiving and storing three-dimensional (3D) model data of an anatomical structure of a patient in the memory; generating positional information to orient 3D model data of the anatomical structure; identifying at least one segment of the 3D model data of the anatomical structure based on the positional information; using an identification enhancer that visually distinguishes at least one identified segment to demarcate the at least one identified segment of the 3D model data of the anatomical structure; and providing, for display, the 3D model data of the anatomical structure having the at least one demarcated segment.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] (Cross - Reference to Related Applications) This application claims the benefit of U.S. Provisional Patent Application No. 62 / 954,194, filed on December 27, 2019, which is hereby incorporated by reference in its entirety as if fully set forth herein.

[0002] (Field of the Invention) This application provides methods, apparatuses, systems, and programs for improving the definition of the boundaries of anatomical structures for visualization.

Background Art

[0003] For medical treatment and investigation, clinical workflows, and research purposes, it is necessary to clearly identify segments of the anatomical structures of individual patients, such as human organs. Since anatomical structures such as heart chambers are typically unique to an individual, the variation between corresponding anatomical structures in different individuals inhibits the use of automated tools for accurately identifying different segments of such structures in a rapid and efficient manner.

[0004] Conventionally, the identification of segments of anatomical structures such as the left atrium has been performed manually by medical experts or researchers. However, such manual identification is time - consuming, inefficient, and may require the use of special 3D editing software.

[0005] The rapid and automated identification of segments of anatomical structures can be important for treating certain conditions. For example, heart diseases such as arrhythmias (e.g., atrial fibrillation) are associated with abnormal conduction in heart tissue. Treatments for heart diseases include identifying the source of signals that cause arrhythmias and interrupting the conduction pathway of the problematic signals. It is possible to block the propagation of unwanted electrical signals by selectively ablating heart tissue. For example, electrical pulmonary vein isolation from the left atrium is performed using ablation to treat atrial fibrillation. Pulmonary vein isolation, and many other minimally invasive catheter-based procedures, require real-time visualization and mapping of the left atrial segments.

Summary of the Invention

Problems to be Solved by the Invention

[0006] In the art, there is a need to accurately identify different segments of anatomical structures that are unique to each individual in an automated manner in order to reduce the time and human error involved in such identification.

Means for Solving the Problems

[0007] Methods, devices, systems, and programs for improving the definition of the boundaries of anatomical structures for visualization are described herein.

[0008] According to one aspect, the subject matter disclosed herein relates to a method for automatically defining boundaries of segments of an anatomical structure, including providing a processor having a memory, receiving and storing three-dimensional (3D) model data of a patient's anatomical structure in the memory, generating position information for orienting the 3D model data of the anatomical structure, identifying at least one segment of the 3D model data of the anatomical structure based on the position information, defining boundaries of at least one identified segment of the 3D model data of the anatomical structure using an identification enhancer that visually differentiates the at least one identified segment, and providing, for display, 3D model data of the anatomical structure having at least one segment with defined boundaries.

[0009] According to another aspect, the method further includes generating a skeletal axis of the 3D model data of the anatomical structure, and the position information for orienting the 3D model data of the anatomical structure is generated based on the skeletal axis.

[0010] According to another aspect, the anatomical structure is a patient's organ. According to yet another aspect, the anatomical structure is a patient's ventricle. According to yet another aspect, the anatomical structure is the left atrium of a patient's heart.

[0011] According to yet another aspect, at least one segment includes at least one pulmonary vein. According to yet another aspect, the skeletal axis includes at least one branch line corresponding to at least one pulmonary vein.

[0012] According to yet another aspect, the 3D model data of the anatomical structure includes a surface mesh.

[0013] According to yet another aspect, at least one pulmonary vein is identified by identifying all points on the surface mesh having a similar Euclidean distance from at least one branch line of the skeletal axis to the surface mesh.

[0014] According to yet another aspect, at least one segment includes at least one of the right superior pulmonary vein, the right inferior pulmonary vein, the left superior pulmonary vein, the left inferior pulmonary vein, and the left atrial appendage. According to yet another aspect, at least one segment includes at least one of the following segments of the left atrium: the left atrial appendage, the roof, the posterior wall, the septum, the anterior wall, the lateral wall, and the bottom wall.

[0015] According to yet another aspect, generating position information that orients the anatomical structure further includes accessing a database that stores information from known mappings of similar anatomical structures. According to yet another aspect, generating the position information includes identifying at least one of the right side, left side, upper side, lower side, posterior side, and anterior side of the 3D model data of the anatomical structure.

[0016] According to yet another aspect, identifying at least one segment of the 3D model data of the anatomical structure further includes generating a graphic cube around the 3D model data of the anatomical structure, the graphic cube including a right face, a left face, an upper face, a bottom face, a posterior face, and an anterior face corresponding to the respective right side, left side, upper side, lower side, posterior side, and anterior side of the 3D model data of the anatomical structure.

[0017] According to yet another aspect, identifying at least one segment of the 3D model data of the anatomical structure further includes projecting at least one of the right face, left face, upper face, bottom face, posterior face, and anterior face of the graphic cube onto the respective right side, left side, upper side, lower side, posterior side, and anterior side of the 3D model data of the anatomical structure.

[0018] According to yet another aspect, the identification enhancer includes at least one of color, line shading, shading, and contrast.

[0019] According to yet another aspect, a display is provided for displaying 3D model data of an anatomical structure having at least one segment defined by at least one boundary.

[0020] According to yet another aspect, 3D model data of a patient's anatomical structure is obtained from an imaging system. In one aspect, the imaging system includes magnetic resonance imaging (MRI), computed tomography (CT) methods, X-ray imaging, rotational angiography, ultrasonic imaging, three-dimensional ultrasonic imaging, or three-dimensional mapping.

[0021] According to yet another aspect, the subject matter disclosed herein relates to an apparatus for automatically defining boundaries of segments of an anatomical structure, including a processor having a memory. The processor is configured to receive and store in the memory three-dimensional (3D) model data of a patient's anatomical structure, generate a skeletal axis of the 3D model data of the anatomical structure, generate position information for orienting the 3D model data of the anatomical structure based on the skeletal axis, identify at least one segment of the 3D model data of the anatomical structure based on the skeletal axis and the position information, and define boundaries of at least one identified segment of the 3D model data of the anatomical structure using an identification enhancer that visually differentiates the at least one identified segment. The apparatus further includes a display in communication with the processor for displaying 3D model data of the anatomical structure having at least one segment with defined boundaries.

[0022] According to yet another aspect, the subject matter disclosed herein relates to a system for automatically defining boundaries of segments of an anatomical structure, including a processor having a memory and a display communicating with the processor. The processor receives and stores in the memory three-dimensional (3D) model data of a patient's anatomical structure, generates a skeletal axis of the 3D model data of the anatomical structure, generates position information for orienting the 3D model data of the anatomical structure based on the skeletal axis, identifies at least one segment of the 3D model data of the anatomical structure based on the skeletal axis and the position information, defines boundaries of at least one identified segment of the 3D model data of the anatomical structure using an identification enhancer that visually differentiates the at least one identified segment, and communicates with the display to display on the display the 3D model data of the anatomical structure having at least one segment with defined boundaries.

[0023] According to yet another aspect, the subject matter disclosed herein is a non-transitory computer-readable recording medium storing program instructions for automatically defining boundaries of segments of three-dimensional (3D) model data of a patient's anatomical structure, the program instructions causing a computer to perform steps of receiving and storing in a memory three-dimensional (3D) model data of a patient's anatomical structure, generating a skeletal axis of the 3D model data of the patient's anatomical structure, generating position information for orienting the 3D model data of the patient's anatomical structure based on the skeletal axis, identifying at least one segment of the 3D model data of the patient's anatomical structure based on the skeletal axis and the position information, defining boundaries of at least one identified segment of the 3D model data of the patient's anatomical structure using an identification enhancer that visually differentiates the at least one identified segment, and providing for display the 3D model data of the patient's anatomical structure having at least one segment with defined boundaries, thereby storing a program for automatically defining boundaries of segments of three-dimensional (3D) model data of a patient's anatomical structure.

Brief Description of the Drawings

[0024] A more detailed understanding will become possible from the following description given as an example together with the accompanying drawings.

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DETAILED DESCRIPTION OF THE INVENTION

[0025] For efficient and accurate visualization of such a structure, a method, system, and program are provided that enable automatic delineation of the boundaries of segments of anatomical structures such as body organs in a unique patient.

[0026] In an exemplary embodiment, the model data of the patient's anatomical structure is automatically segmented and visualized on a display. The model data is preferably three-dimensional model data of the left atrium (LA) of the heart of an individual patient. Although the automatic segmentation of the left atrium is described herein as an exemplary embodiment, those skilled in the art will readily understand that the methods, systems, and programs according to the disclosed subject matter herein can be used to automatically segment and display other organs or anatomical structures and / or portions thereof.

[0027] According to an exemplary embodiment disclosed herein, a system is provided that receives model data of a patient's anatomical structure. The model data can be obtained by an imaging system such as magnetic resonance imaging (MRI), computed tomography (CT) method, X-ray imaging, rotational angiography, ultrasonic imaging, three-dimensional ultrasonic imaging, three-dimensional mapping, or other means for two-dimensional imaging, three-dimensional imaging, and combinations of two-dimensional and three-dimensional imaging. The system preferably includes a processing device having a communication device that receives model data of the patient's anatomical structure. When receiving the model data, the processing device preferably orients the anatomical structure, for example, by generating a skeletal axis of the anatomical structure, identifies easily recognizable structures such as major veins, and progressively enhances segments of the anatomical structure using an identification enhancer. The identification enhancer preferably differentiates and, without limitation, can be based on color, shading, gradient, contrast, etc. The identification enhancer is preferably overlaid on the model data and displayed on a display.

[0028] Referring to FIG. 1, an exemplary system 100 is provided that enables the automatic delineation of the boundaries of segments of the anatomical structure of an individual patient. System 100 preferably includes a processing device 102. The processing device 102 can control the other components of the system 100 in accordance with the embodiments described herein. According to an exemplary embodiment, the processing device 102 may include a memory 104. The memory 104 may comprise any suitable volatile and / or non-volatile memory, such as, for example, random-access memory (RAM), registers, cache memory, semiconductor memory devices, magnetic media, such as internal hard disks and removable disks, magneto-optical media, and optical media, such as CD-ROM disks and digital versatile disks (DVDs). The processing device 102 preferably executes a software program and / or a program stored in hardware to perform the functions required by the system 100. The processing device 102 may execute a software program stored in the memory 104. The software may be downloaded to the processing device 102 in electronic form via a network or may be provided on a tangible medium, such as an optical, magnetic, or other non-volatile storage medium.

[0029] According to an exemplary embodiment, the processing device 102 can be implemented in a general-purpose computer, a dedicated computer, a processor, or a processor core. Suitable processors include, by way of example, a general-purpose processor, a dedicated processor, a conventional processor, a digital signal processor (DSP), a plurality of microprocessors, one or more microprocessors associated with a DSP core, a controller, a microcontroller, an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) circuit, any other type of integrated circuit (IC), and / or a state machine. Such a processor can be manufactured by configuring a manufacturing process using the results of other intermediate data such as processed hardware description language (HDL) instructions and netlists (such instructions can be stored on a computer-readable medium). The result of such processing can be a mask work, which is then used in a semiconductor manufacturing process to manufacture a processor that implements the methods described herein.

[0030] According to an exemplary embodiment, the processing device 102 preferably includes a communication device 106 configured to receive model data 108 of a patient's anatomical structure, such as three-dimensional model data of an organ or a part of an organ obtained by an imaging system 107, such as by magnetic resonance imaging (MRI), computed tomography (CT) method, X-ray imaging, rotational angiography, ultrasonic imaging, three-dimensional ultrasonic imaging, three-dimensional mapping, or other means for two-dimensional imaging, three-dimensional imaging, and combinations of two-dimensional and three-dimensional imaging. The communication device 106 preferably receives the model data 108 from a data transmission device 109 that can be integrated with the imaging system 107 or is separate from but can communicate with the imaging system 107. The communication device 106 can have a wired or wireless connection with the data transmission device 109, or can receive the model data 108 via the Internet or a network. The network can be any network or system generally known in the art, such as an intranet, local area network (LAN), wide area network (WAN), metropolitan area network (MAN), direct connection or series of connections, cellular telephone network, or any other network or medium capable of facilitating communication with the processing device 102. The network can be wired, wireless, or a combination thereof. The wired connection can be implemented using Ethernet, Universal Serial Bus (USB), RJ-11, or any other wired connection generally known in the art. The wireless connection can be implemented using Wi-Fi, WiMAX, and Bluetooth, infrared, cellular network, satellite, or any other wireless connection method generally known in the art.

[0031] According to an exemplary embodiment, the model data 108 can be electronic data derived from imaging a patient's anatomical structure. In an exemplary embodiment, the model data 108 is three-dimensional (3D) model data derived from an image of a patient's organ such as the left atrium of the heart. When the processing device receives the model data 108, the model data 108 can be stored in the memory 104.

[0032] According to an exemplary embodiment, the processing device 102 can be coupled to the display 110 to generate a visual representation of the model data 108. The display 110 may be integrated with the processing device 102 or may be external to the processing device 102.

[0033] According to an exemplary embodiment, the processing device 102 can transmit or receive information from the database 112. The database 112 may be a storage device (auxiliary storage device) that stores various types of pre-determined information. In an exemplary embodiment, the database 112 can be integrated with the processing device 102 such as a storage medium fixed internally (e.g., built-in memory, etc.) or a removable storage medium (e.g., removable card-type memory, etc.). However, the configuration of the database 112 is not limited to such forms. In another exemplary embodiment, the database 112 can be constituted by an external storage device in an independent form. In this case, the database 112 is external to the processing device 102, and the processing device 102 includes a communication unit such as a communication device 106 that enables the transmission and reception of various types of information to / from the database 112.

[0034] According to an exemplary embodiment, the database 112 stores information such as position information, orientation information, or structural information of anatomical structures. For example, the database 112 may store information regarding the orientation of an organ such as the left atrium of the heart. The database 112 may also store information for identifying and arranging known structures within organs such as, but not limited to, veins, chambers, walls, arteries, muscles, tendons, inner walls, layers, etc., which can be used to map segments of a patient's organ such as the left atrium. In an exemplary embodiment, the processing device 102 can utilize information from the database 112 to identify easily recognizable structures such as pulmonary veins within an image of the patient's left atrium. Using the position of the veins, other segments of an organ such as the left atrium of the heart can be identified, as will be described in more detail below.

[0035] In an exemplary embodiment, in accordance with known methods of graphic modeling, the processing device 102 preferably orients the anatomical structure by generating a surface mesh of the anatomical structure in the model data 108, such as a polygonal mesh, more preferably a triangular mesh, of the anatomical structure 108. Alternatively, the model data 108 of the anatomical structure received from the data transmission device 109 may already have a surface mesh generated thereon.

[0036] In an exemplary embodiment, the processing device 102 preferably generates a central axis or principal axis along the central portion of the structure and generates a skeletal axis or local skeleton of the anatomical structure, preferably by known methods and algorithms for generating a skeletal axis, such as by contracting or collapsing the surface mesh of the model data 108 of the anatomical structure to generate any extension branch portions, such as, but not limited to, veins, arteries, accessory organs, etc. Those skilled in the art will recognize that other known methods or algorithms for generating a skeletal axis may be utilized within the scope of the present application.

[0037] In an exemplary embodiment, the processing device 102 preferably orients the anatomical structures in the model data 108 by identifying three-dimensional sides such as, but not limited to, the posterior, anterior, superior, inferior, right, and left sides of the anatomical structure. In a non-limiting example, when model data 108 is generated for a patient, the processing device can identify the posterior, anterior, superior, inferior, right, and left sides of the model data 108 of the patient's anatomical structure by receiving data that identifies the position of the patient's body or organ relative to the imaging system 109. Alternatively, the processing device 102 can identify the posterior, anterior, superior, inferior, right, and left sides of the model data 108 of the patient's anatomical structure by communicating with the database 112 to compare the skeletal axis of the model data 108 with a known anatomical mapping of a similar anatomical structure in a database containing such known anatomical mappings.

[0038] In an exemplary embodiment, the processing device 102 depends on the skeletal axis and the orientation of the anatomical structure to automatically identify segments of the anatomical structure, and progressively enhances the identified segments of the anatomical structure with an identification enhancer, as will be described in detail below. The identification enhancer is preferably overlaid or superimposed on the model data 108 of the anatomical structure to visually distinguish individual segments of the anatomical structure and is displayed on the display 110.

[0039] Figure 2 is an exemplary embodiment of a process 200 for generating and displaying an anatomical structure having segments with automatically defined boundaries using the system 100 described herein. Specifically, Figure 2 illustrates an exemplary process 200 for generating and displaying three-dimensional model data of the left atrium (LA) 300 (Figure 3) of the heart having segments with automatically defined boundaries using the system 100 described herein. More specifically, Figure 2 illustrates an exemplary process 200 for generating and displaying the left atrium of the heart with at least the following segments: right superior pulmonary vein (RSPV), right inferior pulmonary vein (RIPV), left superior pulmonary vein (LSPV), left inferior pulmonary vein (LIPV), left atrial appendage (LAA), canopy, posterior wall, septum, anterior wall, lateral wall, and bottom wall, with automatically defined boundaries.

[0040] In step 202 of Figure 2, the processing device 102 receives model data of the patient's left atrium 300 via the communication device 106. As described above, the model data of the patient's left atrium 300 can be obtained by an imaging system such as magnetic resonance imaging (MRI), computed tomography (CT) method, X-ray imaging, rotational angiography, ultrasonic imaging, three-dimensional ultrasonic imaging, three-dimensional mapping, or other means for two-dimensional imaging, three-dimensional imaging. Figures 3 and 4A show exemplary embodiments of a rear view of three-dimensional (3D) model data of the patient's left atrium 300 of the heart, and Figure 4B shows an exemplary embodiment of a front view of the 3D model data of the left atrium 300. The 3D model data of the left atrium 300 can be displayed on the display 110. In an exemplary embodiment, the 3D model data of the left atrium 300 can be generated as a surface mesh such as a polygonal mesh, more preferably a triangular mesh.

[0041] In step 204 of FIG. 2, the processing device 102 preferably orients the 3D model data of the left atrium 300. For example, but not limited to, the processing device 102 preferably generates a skeletal axis of the 3D model data of the left atrium 300 and orients the 3D model data of the left atrium 300. FIGS. 3, 4A, and 4B show exemplary embodiments of the skeletal axes displayed on the 3D model data of the left atrium 300 including the main axis 301 and five branch axes, including the right superior pulmonary vein (RSPV) axis 302, the right inferior pulmonary vein (RIPV) axis 304, the left superior pulmonary vein (LSPV) axis 306, the left inferior pulmonary vein (LIPV) axis 308, and the left atrial appendage (LAA) axis 310. The processing device 102 then preferably identifies the three-dimensional orientation information of the left atrium within the 3D model data of the left atrium 300. For example, but not limited to, when the model data 301 is generated, the processing device 102 can establish the right, left, lower, posterior, and anterior sides of the 3D model of the left atrium 300 based on the known position of the patient's heart relative to the imaging system 107. Alternatively, the processing device 102 communicates with the database 112 to compare the skeletal axes (301, 302, 304, 306, 308, 310) of the 3D model data of the left atrium 300 with information from a database 112 containing known mapping information of the left atrium, thereby identifying the posterior, anterior, top, bottom, right, and left sides of the 3D model data of the patient's left atrium 300.

[0042] In step 206 of FIG. 2, the processing device 102 preferably places well-recognized structures within the 3D model data of the left atrium 300 based on the skeletal axes 301, 302, 304, 306, 308, 310 and the orientation information. In an exemplary embodiment, the well-recognized structures include, but are not limited to, major veins such as the right superior pulmonary vein (RSPV) 312, the right inferior pulmonary vein (RIPV) 314, the left superior pulmonary vein (LSPV) 316, the left inferior pulmonary vein (LIPV) 318, and the left atrial appendage (LAA) 320 as shown in FIGS. 4A and 4B.

[0043] In an exemplary embodiment shown in FIG. 4A, the pulmonary veins 312, 314, 316, 318 and LAA 320 can be identified by orienting the 3D model data of the left atrium 300 in a rear view and identifying two main branches of the right skeletal axis 302 that become the RSPV 312 and RIPV 314. Using the upper branch of the skeletal axes 302, 304 or the RSPV axis 302, the RSPV 312 and the lower branch can be identified, or using the RIPV axis 304 of the skeletal axis, the RIPV 314 can be identified. Similarly, the three main branches of the skeletal axes 306, 308, 310 on the left side of the 3D model data of the left atrium 300 are used to identify the LSPV 316, LIPV 318 and LAA 320. The upper branch of the skeletal axis or the LSPV axis 306 is used to identify the LSPV 316, the lower branch of the skeletal axis or the LIPV axis 308 is used to identify the LIPV 318, and the middle branch or the LAA axis 310 of the skeletal axis is used to identify the LAA 320. The rear view of the 3D model data of the left atrium 300 is used in the foregoing non-limiting example to illustrate the process of identifying the pulmonary veins and LAA. Those skilled in the art will recognize that the 3D model data of the left atrium 300 can be oriented in any view to perform this identification. For example, FIG. 4B shows an exemplary embodiment of a front view of the 3D model data of the left atrium 300 showing the identified pulmonary veins 312, 314, 316, 318 and LAA 320.

[0044] In another exemplary embodiment, the processing device 102 can orient the 3D model data of the left atrium 300 without generating the skeletal axis of the 3D model data of the left atrium 300 as described in steps 204 and 206 of FIG. 2. Instead, the processing device 102 can identify the RSPV 312, RIPV 314, LSPV 316, LIPV 318 and the left atrial appendage LAA 320 by communicating with the database 112 to compare the 3D model data of the left atrium 300 with the information from the database 112 that includes the known mapping information of the left atrium.

[0045] In step 208 of FIG. 2, the processing device 102 preferably establishes that the pulmonary veins 312, 314, 316, 318 and the LAA 320 are integrated with the main body 321 of the left atrium and define the boundaries of the pulmonary veins 312, 314, 316, 318 and the LAA 320 in the 3D model data of the left atrium together with the identification enhancer. According to an exemplary embodiment, to define the boundaries of the pulmonary veins 312, 314, 316, 318 and the LAA 320, the processing device 102 preferably identifies a pair of branch axes of the skeletal axis having a common branch point from the main axis 301, such as the RSPV axis 302 - RIPV axis 304, the LSPV axis 306 - LIPV axis 308, and the LSPV axis 306 - LAA axis 310. For each identified pair of branch axes, the processing device 102 identifies all points P on the surface mesh of the 3D model data of the left atrium 300 having a similar Euclidean distance from each pair of branch axes to the surface mesh. a The point P on the surface mesh of each of the pulmonary veins 312, 314, 316, 318 and the LAA 320 closest to the center point 311 of the main axis 301 a defines the boundary P between the main body 321 of the left atrium and each of the pulmonary veins 312, 314, 316, 318 and the LAA 320. b The boundary P b preferably coincides with the common branch point between the pair of branch axes and the main axis 301. The point P on the surface mesh of the 3D model data of the left atrium 300 a is used to define the boundaries of the pulmonary veins 312, 314, 316, 318 and the LAA 320 within each boundary P. b The process for identifying the pulmonary veins 312, 314, 316, 318 and the LAA 320 described above is scheduled to start by identifying the "pair of branch axes" of the skeletal axis, but those skilled in the art will understand that it is also possible to perform the processing individually for each branch axis 302, 304, 306, 308, 310.

[0046] In a preferred embodiment, the processing device 102 preferably superimposes an identification enhancer on each of the pulmonary veins 312, 314, 316, 318 and the LAA 320 identified in the 3D model data to define their boundaries and distinguish them for visual recognition. The identification enhancer can be, but is not limited to, color, line shading, shading, contrast, or any other means for visually distinguishing. The identification enhancer is preferably superimposed on the 3D model data of the left atrium 300 and displayed on the display 110. FIGS. 4A and 4B show an exemplary embodiment in which the identification enhancer is superimposed on a segment of the 3D model data of the left atrium, including the RSPV 312, RIPV 314, LSPV 316, LIPV 318 and the LAA 320. As described herein, the identification enhancer visually distinguishes the pulmonary veins 312, 314, 316, 318 and the LAA 320 from each other.

[0047] In step 210 of FIG. 2, the processing device 102 preferably generates a graphic cube 500 around the 3D model data of the left atrium 300 to assist in the process of segment boundary definition shown in FIGS. 5-12. The graphic cube 500 includes a rear surface 502, a front surface 504, an upper surface 506, a bottom surface 508, a right surface 510, and a left surface 512. The process of segment boundary definition is further described in steps 212-222 of FIG. 2.

[0048] In one embodiment, the graphic cube is preferably generated by creating a rectangle for the upper surface 506 where the rectangular vertices are arranged adjacent to the RSPV 312, RIPV 314, LSPV 316 and LIPV 318. The upper surface 506 forms a 3D graphic cube 500 where the bottom surface 508 is adjacent to the lowest point of the 3D model data of the left atrium 300 (see FIG. 6).

[0049] In step 212 of FIG. 2, the processing device 102 identifies the atrial dome segment 322 of the left atrium within the 3D model data of the left atrium 300. The processing device 102 preferably identifies the respective boundaries P of the RSPV 312, RIPV 314, LSPV 316, and LIPV 318 adjacent to the upper surface 506 of the graphic cube 500, respectively. bThe canopy segment 322 is identified by orienting the surface within the surface mesh of the 3D model data of the lower atrium 300. In an exemplary embodiment, as shown in FIG. 13, the relative positions of the RSPV 312, RIPV 314, LSPV 316, and LIPV 318 preferably form corresponding corner points 312a, 314a, 316a, and 318a within the upper surface 506 of the graphic cube 500. In an exemplary embodiment, the processing device divides the upper surface 506 by generating a line L parallel to the edge formed by the corners 312a - 316a and the edge formed by the corners 314a - 318a. The line L is preferably generated in a way that divides the surface area representing the canopy segment 322a from the surface area representing the posterior wall segment 324a on the upper surface 506 of the graphic cube 500, based on a predetermined surface area from a known 3D mapping of the canopy segment to the posterior wall. In an exemplary embodiment, the processing device 102 can access the database 112 to obtain the predetermined surface area. In an exemplary embodiment, the upper surface 506 of the graphic cube is divided by the line L such that the surface area representing the canopy segment 322a is smaller than the surface area representing the posterior wall 324a. In one embodiment, the surface area representing the canopy segment 322a is about 20% - 30% of the surface area of the upper surface 506, and the surface area representing the posterior wall 324a is about 70% - 80% of the surface area of the upper surface 506. Those skilled in the art will recognize that the aforementioned percentages of the surface area of the upper surface 506 can be modified based on the specific anatomical structure or organ in the target model data 1098. In an exemplary embodiment, the smaller surface area 322a of the upper surface 506 of the graphic cube 500 is projected onto the surface mesh of the 3D model of the lower atrium 300 to define the boundaries of the canopy segment 322. Upon identification, the canopy segment 322 is preferably shown using identification enhancers such as color, line shading, shading, contrast, etc. for visual identification of the canopy segment 322 on the display 110, as shown in FIGS. 6, 7, 8, and 10.

[0050] In step 214 of FIG. 2, the processing device 102 identifies the posterior wall segment 324 of the left atrium within the 3D model data of the left atrium 300. The processing device 102 preferably uses the process described above with respect to the identification of the canopy segment 322 to identify the segment of the left atrium adjacent to the canopy segment 322 and between the boundaries P of the RSPV 312, RIPV 314, LSPV 316, and LIPV 318 to identify the posterior wall segment 324. Specifically, the larger surface area 324a of the upper surface 506 of the graphic cube 500 is projected onto the surface mesh of the 3D model of the lower atrium 300 to define the boundaries of the posterior wall segment 324. Upon identification, the posterior wall segment 324 is preferably shown using an identification enhancer for visually identifying the posterior wall segment 324 on the display 110 as shown in FIGS. 6-8, 10, and 12. b By identifying the segment of the left atrium between the boundaries P of the RSPV 312, RIPV 314, LSPV 316, and LIPV 318 adjacent to the canopy segment 322, the posterior wall segment 324 is identified. Specifically, the larger surface area 324a of the upper surface 506 of the graphic cube 500 is projected onto the surface mesh of the 3D model of the lower atrium 300 to define the boundaries of the posterior wall segment 324. Upon identification, the posterior wall segment 324 is preferably shown using an identification enhancer for visually identifying the posterior wall segment 324 on the display 110 as shown in FIGS. 6-8, 10, and 12.

[0051] In step 216 of FIG. 2, the processing device 102 identifies the septal segment 326 of the left atrium within the 3D model data of the left atrium 300. The processing device 102 preferably projects the right surface 510 of the graphic cube 500 onto the surface mesh of the 3D model of the lower atrium 300 and identifies the segment of the left atrium adjacent to the RSPV 312 and RIPV 314 as the septal segment 326 to identify the septal segment 326. Upon identification, the septal segment 326 is preferably shown using an identification enhancer for visually identifying the septal segment 326 on the display 110 as shown in FIGS. 6-12.

[0052] In step 218 of FIG. 2, the processing device 102 identifies the anterior wall segment 328 of the left atrium within the 3D model data of the left atrium 300. The processing device 102 preferably projects the front face 504 of the graphic cube 500 onto the surface mesh of the 3D model of the lower atrium 300, and identifies the anterior wall segment 328 by identifying the segments of the left atrium adjacent to the RSPV 312, LAA 320, canopy segment 322, and septal segment 326 as the anterior wall segment. Upon identification, the anterior wall segment 328 is preferably shown using an identification enhancer for visually identifying the anterior wall segment 328 on the display 110, as shown in FIGS. 7, 9, and 10.

[0053] In step 220 of FIG. 2, the processing device 102 identifies the lateral wall segment 330 of the left atrium within the 3D model data of the left atrium 300. The processing device 102 preferably projects the left face 512 of the graphic cube 500 onto the surface mesh of the 3D model of the lower atrium 300, and identifies the lateral wall segment 330 by identifying the segments of the left atrium adjacent to the LSPV 316, LIPV 318, LAA 320, and LAA 320, as well as the anterior wall segment 328, as the lateral wall segment. Upon identification, the lateral wall segment 330 is preferably shown using an identification enhancer for visually identifying the lateral wall segment 330 on the display 110, as shown in FIGS. 6-8, 10, and 12.

[0054] In step 222 of FIG. 2, the processing device 102 identifies the bottom wall segment 332 of the left atrium within the 3D model data of the left atrium 300. The processing device 102 preferably projects the bottom surface 508 of the graphic cube 500 onto the surface mesh of the 3D model of the lower atrium 300 and identifies the segment of the left atrium adjacent to the RIPV 316, LIPV 318, LAA 320, posterior wall segment 324, anterior wall segment 328, septal segment 326, and lateral wall segment 330 as the bottom wall segment 332, thereby identifying the bottom wall segment 332. Upon identification, the bottom wall segment 332 is preferably shown using an identification enhancer for visually identifying the bottom wall segment 332 on the display 110.

[0055] After step 222, the processing device expands the boundaries of each segment until they contact other segments and fills the 3D model data of the left atrium 300 with an identification enhancer to visually distinguish the segments with defined boundaries.

[0056] In step 224 of FIG. 2, the segmented 3D model data of the left atrium 300 is preferably displayed on the display 110 showing different identification enhancers to visually distinguish the segments with defined boundaries. Those skilled in the art will readily understand that different identification enhancers, such as different colors, can be used to visually distinguish the various identified structures.

[0057] According to an exemplary embodiment, each or any of steps 204 - 224 of process 200 can be progressively displayed on the display 110 between each step of process 200.

[0058] Those skilled in the art will readily understand that steps 204 - 224 of process 200 can be progressively executed in any preferred order, specific steps of process 200 can be excluded, or additional process steps can be added to identify other segments of the left atrium not specifically mentioned herein.

[0059] FIGS. 2-13 and the disclosure of this specification relate to an exemplary process 200 for generating and displaying a left atrium (LA) of a heart having automatically defined segments using the system 100 described herein. One of ordinary skill in the art will readily understand that the disclosed process can be applied to automatically segment and display other organs or anatomical structures.

[0060] The subject matter disclosed herein for automatically defining the boundaries of anatomical structures provides more accurate and predictable data by reducing the time involved in segmenting anatomical structures and minimizing human error compared to conventional techniques that require manual segmentation.

[0061] It should be understood that many variations are possible based on the disclosure of this specification. Although features and elements are described above in specific combinations, each feature or element may be used alone without other features and elements, or in various combinations with other features and elements with or without other features and elements. Similarly, although process steps are described above in a particular order, the steps can be performed in other desirable orders.

[0062] The methods, processes, and / or flowcharts provided herein can be implemented in a computer program, software, or firmware incorporated into a non-transitory computer-readable storage medium for implementation by a general-purpose computer or processor. Examples of non-transitory computer-readable storage media include ROM, random access memory (RAM), registers, cache memory, semiconductor memory devices, magnetic media such as internal hard disks and removable disks, magneto-optical media, and optical media such as CD-ROM disks and digital versatile disks (DVDs).

[0063] Certain specialized terms are used in the description of this specification merely for convenience and are not limiting. The terms "right", "left", "upper", "lower", "front", and "rear" indicate directions in the drawings for reference. The terms "a" and "one", when used in the claims and corresponding parts of this specification, are defined as including one or more of the items referred to, unless otherwise specified. This specialized terminology includes the terms specifically mentioned above, their derivatives, and terms with similar meanings. When a listing of two or more items such as "A, B, or C" follows the phrase "at least one", it means any individual one of A, B, or C and any combination thereof.

[0064] Further exemplary embodiments of this specification may be formed by adding one or more elements derived from any one or more other embodiments of this specification to a certain embodiment and / or by replacing one or more elements derived from a certain embodiment with one or more elements derived from one or more other embodiments of this specification.

[0065] Therefore, it is understood that the disclosed subject matter is not limited to the specific embodiments disclosed, but is intended to cover all modifications within the spirit and scope of the present invention as defined by the appended claims, the above description, and / or shown in the appended drawings.

[0066] 〔Embodiment〕 (1) A method for automatically defining the boundaries of segments of an anatomical structure, comprising: providing a processor having a memory; receiving and storing three-dimensional (3D) model data of a patient's anatomical structure in the memory; generating position information for orienting the 3D model data of the anatomical structure; identifying at least one segment of the 3D model data of the anatomical structure based on the position information; Using an identification enhancer that visually distinguishes the at least one identified segment, defining the boundary of the at least one identified segment of the 3D model data of the anatomical structure; Providing, for display, the 3D model data of the anatomical structure having the at least one segment with a defined boundary; A method comprising. (2) Generating a skeletal axis of the 3D model data of the anatomical structure; Further comprising, The method according to embodiment 1, wherein the position information for orienting the 3D model data of the anatomical structure is generated based on the skeletal axis. (3) The method according to embodiment 1, wherein the anatomical structure is the left atrium of the patient's heart and the at least one segment includes at least one pulmonary vein. (4) The skeletal axis includes at least one branch corresponding to the at least one pulmonary vein, The 3D model data of the anatomical structure includes a surface mesh, The method according to embodiment 3, wherein the at least one pulmonary vein is identified by identifying all points on the surface mesh having a similar Euclidean distance from the at least one branch of the skeletal axis to the surface mesh. (5) The method according to embodiment 1, wherein the at least one segment includes at least one of a right superior pulmonary vein, a right inferior pulmonary vein, a left superior pulmonary vein, a left inferior pulmonary vein, and a left atrial appendage, a canopy, a posterior wall, a septum, an anterior wall, a lateral wall, and a bottom wall.

[0067] (6) Generating the position information for orienting the anatomical structure further includes Accessing a database storing information from a known mapping of similar anatomical structures, Identifying at least one of a right side, a left side, an upper side, a lower side, a posterior side, and an anterior side of the 3D model data of the anatomical structure; The method according to embodiment 1. (7) Identifying at least one segment of the 3D model data of the anatomical structure further includes generating a graphic cube around the 3D model data of the anatomical structure, the graphic cube including a right face, a left face, an upper face, a bottom face, a rear face, and a front face corresponding to the right side, the left side, the upper side, the lower side, the rear side, and the front side, respectively, of the 3D model data of the anatomical structure, the method according to embodiment 6. (8) Identifying at least one segment of the 3D model data of the anatomical structure further includes projecting at least one of the right face, the left face, the upper face, the bottom face, the rear face, and the front face of the graphic cube onto the right side, the left side, the upper side, the lower side, the rear side, and the front side, respectively, of the 3D model data of the anatomical structure, the method according to embodiment 7. (9) The method according to embodiment 1, wherein the identification enhancer includes at least one of color, line shading, shading, and contrast. (10) The method according to embodiment 1, wherein the 3D model data of the anatomical structure is obtained from an imaging system.

[0068] (11) A system for automatically defining boundaries of segments of an anatomical structure, a processor including a memory, a display communicating with the processor and comprising: the processor is configured to receive and store three-dimensional (3D) model data of a patient's anatomical structure in the memory, generate a skeletal axis of the 3D model data of the anatomical structure, generate position information for orienting the 3D model data of the anatomical structure based on the skeletal axis, identify at least one segment of the 3D model data of the anatomical structure based on the skeletal axis and the position information, Using an identification enhancer that visually distinguishes the at least one identified segment, define the boundary of the at least one identified segment of the 3D model data of the anatomical structure, communicate with the display and display the 3D model data of the anatomical structure having the at least one segment with the defined boundary on the display A system configured as follows. (12) The system according to embodiment 11, wherein the anatomical structure is the left atrium of the patient's heart, and the at least one segment includes at least one of the right superior pulmonary vein, the right inferior pulmonary vein, the left superior pulmonary vein, the left inferior pulmonary vein, and the left atrial appendage, the canopy, the posterior wall, the septum, the anterior wall, the side wall, and the bottom wall. (13) The system according to embodiment 11, further comprising a database that communicates with the processor to store information from known mappings of similar anatomical structures. (14) The skeletal axis includes at least one branch corresponding to at least one pulmonary vein, the 3D model data of the anatomical structure includes a surface mesh, The system according to embodiment 11, wherein the at least one pulmonary vein is identified by identifying all points on the surface mesh having a similar Euclidean distance from the at least one branch of the skeletal axis to the surface mesh. (15) The processor, generates the position information by identifying at least one of the right side, left side, upper side, lower side, rear side, and front side of the 3D model data of the anatomical structure, identifies at least one segment of the 3D model data of the anatomical structure by generating a graphic cube around the 3D model data of the anatomical structure, the graphic cube including a right face, a left face, an upper face, a bottom face, a rear face, and a front face corresponding to the respective right side, left side, upper side, lower side, rear side, and front side of the 3D model data of the anatomical structure. The system according to embodiment 11.

[0069] A non-transitory computer-readable recording medium storing program instructions for automatically defining boundaries of segments of 3D model data of a patient's anatomical structure, the computer being caused to, receive and store the 3D model data of the patient's anatomical structure of the patient; generate a skeletal axis of the 3D model data of the patient's anatomical structure; generate position information for orienting the 3D model data of the patient's anatomical structure based on the skeletal axis; identify at least one segment of the 3D model data of the patient's anatomical structure based on the skeletal axis and the position information; define boundaries of the at least one identified segment of the 3D model data of the patient's anatomical structure using an identification enhancer that visually differentiates the at least one identified segment; provide, for display, the 3D model data of the patient's anatomical structure having the at least one segment with defined boundaries A non-transitory computer-readable recording medium storing program instructions for automatically defining boundaries of segments of 3D model data of a patient's anatomical structure by causing the above to be executed. (17) The non-transitory computer-readable recording medium according to embodiment 16, wherein the anatomical structure is the left atrium of the patient's heart, and the at least one segment includes at least one of a right superior pulmonary vein, a right inferior pulmonary vein, a left superior pulmonary vein, a left inferior pulmonary vein, and a left atrial appendage, a canopy, a posterior wall, a septum, an anterior wall, a lateral wall, and a bottom wall. (18) The non-transitory computer-readable recording medium according to embodiment 16, further comprising a database communicating with the computer storing information from known mappings of similar anatomical structures. (19) The skeletal axis includes at least one branch corresponding to at least one pulmonary vein, the 3D model data of the patient's anatomical structure includes a surface mesh, The non-transitory computer-readable recording medium according to embodiment 16, wherein the at least one pulmonary vein is identified by identifying all points on the surface mesh having the same Euclidean distance from the at least one branch line of the skeletal axis to the surface mesh. (20) Generating position information for orienting 3D model data of the anatomical structure of the patient further includes identifying at least one of a right side, a left side, an upper side, a lower side, a rear side, and a front side of the 3D model data of the anatomical structure of the patient, The non-transitory computer-readable recording medium according to embodiment 16, wherein identifying at least one segment of the 3D model data of the anatomical structure of the patient further includes generating a graphic cube around the 3D model data of the anatomical structure of the patient, the graphic cube including a right face, a left face, an upper face, a bottom face, a rear face, and a front face corresponding to the respective right side, left side, upper side, lower side, rear side, and front side of the 3D model data of the anatomical structure of the patient.

Claims

**Claim 1** A method for automatically defining boundaries of segments of an anatomical structure, comprising: providing a processor having a memory; receiving and storing in the memory three-dimensional (3D) model data of a patient's anatomical structure; generating position information for orienting the 3D model data of the anatomical structure; identifying at least one segment of the 3D model data of the anatomical structure based on the position information; defining boundaries of the identified at least one segment of the 3D model data of the anatomical structure using an identification enhancer that visually differentiates the identified at least one segment; providing for display the 3D model data of the anatomical structure having at least one segment with defined boundaries; wherein the anatomical structure is the left atrium of the patient's heart, the at least one segment includes at least one pulmonary vein, the skeletal axis of the 3D model data of the anatomical structure includes at least one branch line corresponding to the at least one pulmonary vein, the 3D model data of the anatomical structure includes a surface mesh, and the at least one pulmonary vein is identified by identifying all points on the surface mesh having a similar Euclidean distance from the at least one branch line of the skeletal axis to the surface mesh; a method. **Claim 2** further comprising generating a skeletal axis of the 3D model data of the anatomical structure, wherein the position information for orienting the 3D model data of the anatomical structure is generated based on the skeletal axis, the method according to claim 1. **Claim 3** The method according to claim 1, wherein the at least one segment includes at least one of a right superior pulmonary vein, a right inferior pulmonary vein, a left superior pulmonary vein, a left inferior pulmonary vein, and a left atrial appendage, a canopy, a posterior wall, a septum, an anterior wall, a lateral wall, and a bottom wall. **Claim 4** The method according to claim 1, wherein generating the position information for orienting the anatomical structure further comprises accessing a database storing information from known mappings of similar anatomical structures, and identifying at least one of a right side, a left side, an upper side, a lower side, a posterior side, and an anterior side of the 3D model data of the anatomical structure. **Claim 5** ​ ​ Identifying at least one segment of the 3D model data of the anatomical structure further includes generating a graphic cube around the 3D model data of the anatomical structure, the graphic cube including a right face, a left face, an upper face, a bottom face, a rear face, and a front face corresponding to the respective right side, left side, upper side, lower side, rear side, and front side of the 3D model data of the anatomical structure. The method according to claim 4.

6. Identifying at least one segment of the 3D model data of the anatomical structure further includes projecting at least one of the right face, left face, upper face, bottom face, rear face, and front face of the graphic cube onto the respective right side, left side, upper side, lower side, rear side, and front side of the 3D model data of the anatomical structure. The method according to claim 5.

7. The method according to claim 1, wherein the identification enhancer includes at least one of color, line shading, shading, and contrast.

8. The method according to claim 1, wherein the 3D model data of the anatomical structure is obtained from an imaging system.

9. A system for automatically defining boundaries of segments of an anatomical structure, comprising: a processor including a memory; a display communicating with the processor; The processor: receives and stores in the memory three-dimensional (3D) model data of a patient's anatomical structure; generates a skeletal axis of the 3D model data of the anatomical structure; generates position information for orienting the 3D model data of the anatomical structure based on the skeletal axis; identifies at least one segment of the 3D model data of the anatomical structure based on the skeletal axis and the position information; defines boundaries of the identified at least one segment of the 3D model data of the anatomical structure using an identification enhancer that visually distinguishes the identified at least one segment; communicates with the display to display on the display the 3D model data of the anatomical structure having at least one segment with defined boundaries; The skeletal axis includes at least one branch corresponding to at least one pulmonary vein; The 3D model data of the anatomical structure includes a surface mesh. ​ configured such that the at least one pulmonary vein is identified by identifying all points on the surface mesh having a similar Euclidean distance from the at least one branch line of the skeletal axis to the surface mesh System **Claim 10** The system according to claim 9, wherein the anatomical structure is the left atrium of the patient's heart, and the at least one segment includes at least one of the right superior pulmonary vein, the right inferior pulmonary vein, the left superior pulmonary vein, the left inferior pulmonary vein, and the left atrial appendage, the canopy, the posterior wall, the septum, the anterior wall, the lateral wall, and the bottom wall **Claim 11** The system according to claim 9, further comprising a database communicating with the processor for storing information from known mappings of similar anatomical structures **Claim 12** The processor generates the position information by identifying at least one of the right side, left side, upper side, lower side, posterior side, and anterior side of the 3D model data of the anatomical structure identifies at least one segment of the 3D model data of the anatomical structure by generating a graphic cube around the 3D model data of the anatomical structure, the graphic cube including a right face, a left face, an upper face, a bottom face, a posterior face, and an anterior face corresponding to the respective right side, left side, upper side, lower side, posterior side, and anterior side of the 3D model data of the anatomical structure, the system according to claim 9 **Claim 13** A non-transitory computer-readable recording medium storing program instructions for automatically defining boundaries of segments of three-dimensional (3D) model data of a patient's anatomical structure, the computer performing receiving and storing the three-dimensional (3D) model data of the patient's anatomical structure generating a skeletal axis of the 3D model data of the patient's anatomical structure generating position information for orienting the 3D model data of the patient's anatomical structure based on the skeletal axis identifying at least one segment of the 3D model data of the patient's anatomical structure based on the skeletal axis and the position information defining boundaries of the identified at least one segment of the 3D model data of the patient's anatomical structure using an identification enhancer for visually distinguishing the identified at least one segment providing, for display purposes, the 3D model data of the anatomical structure of the patient having at least one segment defined by at least one of the boundaries storing program instructions for automatically defining boundaries of segments of 3D model data of an anatomical structure of a patient by causing execution thereof a non-transitory computer-readable recording medium, wherein the skeletal axis includes at least one branch corresponding to at least one pulmonary vein, wherein the 3D model data of the anatomical structure of the patient includes a surface mesh, wherein the at least one pulmonary vein is identified by identifying all points on the surface mesh having a similar Euclidean distance from the at least one branch of the skeletal axis to the surface mesh, the non-transitory computer-readable recording medium

14. The non-transitory computer-readable recording medium according to claim 13, wherein the anatomical structure is the left atrium of the patient's heart, and the at least one segment includes at least one of a right superior pulmonary vein, a right inferior pulmonary vein, a left superior pulmonary vein, a left inferior pulmonary vein, and a left atrial appendage, a canopy, a posterior wall, a septum, an anterior wall, a lateral wall, and a bottom wall

15. The non-transitory computer-readable recording medium according to claim 13, further comprising a database communicating with the computer storing information from known mappings of similar anatomical structures

16. generating position information for orienting the 3D model data of the anatomical structure of the patient further includes identifying at least one of a right side, a left side, an upper side, a lower side, a posterior side, and an anterior side of the 3D model data of the anatomical structure of the patient, identifying at least one segment of the 3D model data of the anatomical structure of the patient further includes generating a graphic cube around the 3D model data of the anatomical structure of the patient, the graphic cube including a right face, a left face, an upper face, a bottom face, a posterior face, and an anterior face corresponding to the right side, the left side, the upper side, the lower side, the posterior side, and the anterior side, respectively, of the 3D model data of the anatomical structure of the patient, the non-transitory computer-readable recording medium according to claim 13

17. A method for automatically defining boundaries of segments of an anatomical structure, comprising: providing a processor having a memory; receiving and storing in the memory three-dimensional (3D) model data of an anatomical structure of a patient; Generating position information for orienting the 3D model data of the anatomical structure; Identifying at least one segment of the 3D model data of the anatomical structure based on the position information; Defining boundaries of the identified at least one segment of the 3D model data of the anatomical structure using an identification enhancer that visually differentiates the identified at least one segment; Providing, for display, the 3D model data of the anatomical structure having at least one segment with defined boundaries; comprising; generating position information for orienting the anatomical structure comprises; accessing a database storing information from known mappings of similar anatomical structures; identifying at least one of a right side, a left side, an upper side, a lower side, a posterior side, and an anterior side of the 3D model data of the anatomical structure; further comprising; identifying at least one segment of the 3D model data of the anatomical structure further comprises generating a graphic cube around the 3D model data of the anatomical structure, the graphic cube including a right face, a left face, an upper face, a bottom face, a posterior face, and an anterior face corresponding to the respective right side, left side, upper side, lower side, posterior side, and anterior side of the 3D model data of the anatomical structure, a method. A system for automatically defining boundaries of segments of an anatomical structure, comprising: a processor including a memory; a display in communication with the processor; wherein the processor: receives and stores in the memory three-dimensional (3D) model data of a patient's anatomical structure; generates a skeletal axis of the 3D model data of the anatomical structure; generates position information for orienting the 3D model data of the anatomical structure based on the skeletal axis; identifies at least one segment of the 3D model data of the anatomical structure based on the skeletal axis and the position information; defines boundaries of the identified at least one segment of the 3D model data of the anatomical structure using an identification enhancer that visually differentiates the identified at least one segment; communicates with the display to display on the display the 3D model data of the anatomical structure having at least one segment with defined boundaries; ​ Generating the position information by identifying at least one of the right side, left side, upper side, lower side, rear side, and front side of the 3D model data of the anatomical structure; Identifying at least one segment of the 3D model data of the anatomical structure by generating a graphic cube around the 3D model data of the anatomical structure, the graphic cube being configured to include a right face, a left face, an upper face, a bottom face, a rear face, and a front face corresponding to the right side, the left side, the upper side, the lower side, the rear side, and the front side of the 3D model data of the anatomical structure respectively. A non-transitory computer-readable recording medium storing program instructions for automatically defining boundaries of segments of three-dimensional (3D) model data of a patient's anatomical structure, the computer being caused to: Receive and store the three-dimensional (3D) model data of the patient's anatomical structure; Generate a skeletal axis of the 3D model data of the patient's anatomical structure; Generate position information for orienting the 3D model data of the patient's anatomical structure based on the skeletal axis; Identify at least one segment of the 3D model data of the patient's anatomical structure based on the skeletal axis and the position information; Define boundaries of the identified at least one segment of the 3D model data of the patient's anatomical structure using an identification enhancer that visually differentiates the identified at least one segment; Provide, for display, the 3D model data of the patient's anatomical structure having at least one segment with boundaries defined; By causing to execute, stores program instructions for automatically defining boundaries of segments of 3D model data of a patient's anatomical structure. A non-transitory computer-readable recording medium, wherein generating the position information for orienting the 3D model data of the patient's anatomical structure further includes identifying at least one of the right side, left side, upper side, lower side, rear side, and front side of the 3D model data of the patient's anatomical structure. Identifying at least one segment of the 3D model data of the anatomical structure of the patient further includes generating a graphic cube around the 3D model data of the anatomical structure of the patient, the graphic cube including a right face, a left face, an upper face, a bottom face, a rear face, and a front face corresponding to the respective right side, left side, upper side, lower side, rear side, and front side of the 3D model data of the anatomical structure of the patient, a non-transitory computer-readable recording medium.

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