System and method for area boundary guided coverage of organs

Abstract

The present teachings relate to methods, systems, media, and implementations of area boundary identification and overlay display. Input associated with a 3D object is received. A 3D volumetric model of a 3D object having a plurality of regions is obtained, each region comprising a plurality of tagged voxels. A mesh representation is generated for a surface of the 3D object. Regional boundaries on the surface of the 3D object are identified based on the 3D volumetric model and the mesh representation. And rendering the 3D object, and covering the rendered 3D object with the region boundary.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of priority to U.S. non-provisional patent application No. 18 / 158,360, filed on January 23, 2023, which is incorporated herein by reference in its entirety. Background Art 1. Technical Field

[0002] The present teachings relate generally to computers and more particularly to signal processing. 2. Background Technology

[0003] With advances in computer-related technology, computers are now used to analyze more and more types of information to identify and visualize relevant features, thereby enhancing a user's understanding of important aspects of the information and facilitating the user to make appropriate decisions accordingly. Various industries have benefited from such technological advances, including the medical industry, in which large amounts of image data can be processed to capture a patient's anatomical information to identify regions of interest (e.g., organs, bones, blood vessels, or abnormal nodules), obtain measurements of each region of interest (e.g., the size of a nodule growing in an organ), and visualize relevant features (e.g., three-dimensional (3D) visualization of an abnormal nodule). Such technology enables healthcare professionals (e.g., doctors) to use high-tech means to help them treat patients in a more effective manner.

[0004] In recent years, technologies have been developed to help medical personnel obtain preoperative plans based on image-derived analysis before surgery, or to provide real-time visualization of anatomical structures in a patient's body to guide surgeons during medical procedures. For example, partial hepatectomy is a procedure in which a portion of a patient's liver is removed to remove, for example, a cancer growing in the liver. For this type of surgery, preoperative planning can be performed to identify the area of ​​the liver that needs to be resected. Such pre-planned resection areas can be identified in an offline process and can be marked so that they can be used as a reference for the surgeon to perform the operation during surgery.

[0005] While existing 3D visualization tools can be used to visualize anatomical structures, these general-purpose tools lack functionality tailored to certain medical procedures, which require information to be presented in a certain way to provide useful guidance. Partial hepatectomy is one such procedure. For example, to remove cancer in the liver, surgeons can instantly see what sensors see inside the patient's body on a real-time display to understand the intended resection site. Without such tools, surgeons must rely on general knowledge of liver anatomy and memory to mentally map pre-planned resection boundaries to the actual liver, which increases the difficulty and often leads to inconsistent surgical results.

[0006] Therefore, solutions that can address the above challenges are needed. Summary of the Invention

[0007] The teachings disclosed herein relate to methods, systems, and programming for information management. More specifically, the teachings relate to methods, systems, and programming related to hash tables and storage management using hash tables.

[0008] In one example, a method, implemented on a machine having at least one processor, a storage device, and a communication platform capable of connecting to a network, for region boundary identification and overlay display, receives input associated with a 3D object. A 3D volume model of the 3D object is obtained having a plurality of regions, each region comprising a plurality of labeled voxels. A mesh representation is generated for a surface of the 3D object. Region boundaries are identified on the surface of the 3D object based on the 3D volume model and the mesh representation. The 3D object is rendered, and the region boundaries are overlaid on the rendered 3D object.

[0009] In a different example, a system for region boundary identification and overlay display is disclosed. The system includes a 3D region volume modeling unit, a grid-based region boundary determiner, and a region boundary overlay display unit. The 3D region volume modeling unit is configured to receive input associated with a three-dimensional (3D) object having multiple regions therein and obtain a 3D volume model representing the 3D object, wherein the 3D object includes multiple regions, each region occupies multiple voxels in the 3D volume model, and the voxels of each region in the multiple regions have the same label. The grid-based region boundary determiner is configured to generate a 3D surface mesh representation of a surface representing the 3D object, wherein the 3D surface mesh representation includes multiple connected geometric units, and identifies region boundaries on the surface of the 3D object based on the 3D surface mesh representation and the 3D volume model. The region boundary overlay display unit is configured to render the 3D object on a two-dimensional (2D) display device and overlay the region boundaries of the 3D object on the rendered 3D object.

[0010] Other concepts relate to software for implementing the present teachings. A software product according to this concept includes at least one machine-readable non-transitory medium and information carried by the medium. The information carried by the medium can be executable program code data, parameters associated with the executable program code, and / or information related to a user, a request, content, or other additional information.

[0011] Another example is a machine-readable, non-transitory, tangible medium having recorded thereon information for identifying and overlaying region boundaries. When read by a machine, the information causes the machine to perform the following steps: Receive input associated with a 3D object; Obtain a 3D volume model of the 3D object having a plurality of regions, each region comprising a plurality of labeled voxels; Generate a mesh representation of a surface of the 3D object; Identify region boundaries on the surface of the 3D object based on the 3D volume model and the mesh representation; Render the 3D object, and overlay the region boundaries on the rendered 3D object.

[0012] Additional advantages and novel features will be set forth in part in the following description and in part will be apparent to those skilled in the art upon examination of the following and accompanying drawings, or may be learned by production or operation of the examples. The advantages of the present teachings may be realized and obtained by practice or use of various aspects of the methods, tools, and combinations set forth in the detailed examples discussed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The methods, systems, and / or programs described herein will be further described by way of exemplary embodiments. These exemplary embodiments will be described in detail with reference to the accompanying drawings. These embodiments are non-limiting exemplary embodiments, in which like reference numerals denote similar structures throughout the several views of the drawings, and in which:

[0014] Figure 1A A human liver is shown;

[0015] Figure 1B A human liver with its different lobes is shown;

[0016] Figure 1C An example organ with a malignant growth therein is shown;

[0017] Figure 1D The section of the liver with the malignant growth removed is shown;

[0018] Figure 1E A volumetric representation of the object is shown;

[0019] Figure 1F A mesh representation of the object is shown;

[0020] Figure 1G A mesh representation of the human liver is shown;

[0021] Figure 2A An exemplary high-level system diagram depicting a framework for identifying and rendering boundaries of a resection region of an organ according to an embodiment of the present teachings;

[0022] Figure 2Bis a flow chart of an exemplary process for identifying and rendering a framework of a boundary for resection of an organ according to an embodiment of the present teachings;

[0023] Figure 3 The concept of identifying region boundaries on the surface of an organ using geometric units forming a surface mesh representation of the organ according to an embodiment of the present teachings is shown;

[0024] Figure 4A depicts an exemplary high-level system diagram of a grid-based region boundary determiner according to an embodiment of the present teachings;

[0025] Figure 4B is a flow chart of an exemplary process of a grid-based region boundary determiner according to an embodiment of the present teachings;

[0026] Figure 5 A two-dimensional (2D) display is shown, wherein rendered organs have different anatomical regions and coverage area boundaries, identified according to an embodiment of the present teachings;

[0027] Figure 6 shows a close-up view of a coverage area boundary rendered around a malignant growth in an organ according to an embodiment of the present teachings;

[0028] Figure 7 is a schematic diagram of an exemplary mobile device architecture that can be used to implement a dedicated system for implementing the present teachings in accordance with various embodiments; and

[0029] Figure 8 is a schematic diagram of an exemplary computing device architecture that can be used to implement a special-purpose system for implementing the present teachings in accordance with various embodiments. DETAILED DESCRIPTION

[0030] In the following detailed description, numerous specific details are set forth by way of example in order to facilitate a thorough understanding of the relevant teachings. However, it should be apparent to one skilled in the art that the present teachings may be practiced without these details. In other instances, well-known methods, processes, components, and / or systems have been described at a relatively high level, without detail, in order to avoid unnecessarily obscuring aspects of the present teachings.

[0031] This teaching discloses exemplary methods, systems, and implementations for identifying region boundaries on the surface of a 3D object, wherein the region boundaries isolate different structural regions within the 3D object. Such a 3D object may correspond to an organ such as a liver. The identified region boundaries of the 3D object can be visualized by overlaying them on a rendering of the 3D object. In some embodiments, the region boundaries can be overlaid on a 3D rendering of the 3D object. In some embodiments, the region boundaries can be projected onto a 2D image of the object.

[0032] The region boundaries can be visualized relative to a specific viewing angle, which can be determined based on the viewing angle used to render the 3D object. In some embodiments, when the 3D object is visualized as a 2D image, the viewing angle can be determined based on the viewing angle of the camera used to capture the 2D image. When the 3D object is rendered in 3D, the viewing angle used to visualize the region boundaries can be determined based on the pose parameters used in visualizing the 3D object.

[0033] In some applications of the present teachings, a 3D object may correspond to a human organ such as a liver. Regions within such an object may correspond to liver lobes. In this case, region boundaries divide adjacent lobes of the liver. In applying the present teachings to a partial hepatectomy procedure, the portion of the liver to be removed corresponds to the resection region, and the region boundaries of the resection region represent the boundaries between the lobes to be removed. During the partial hepatectomy procedure, the region boundaries of the resection region can be identified and visualized by overlaying the region boundaries of the resection region onto a rendering of the resection region. This can be done in real time and in a continuous manner, effectively providing a visualization that helps the user always see the location of the portion of the liver intended to be removed.

[0034] The present teachings utilize different representations of 3D objects to determine the location of a boundary that separates different regions of the 3D object. The present teachings can also be applied to specific regions of a 3D object, such as a resection region, to determine the location of a region boundary that separates different regions of a given specific region of the 3D object. In some embodiments, a 3D object (or 3D region) can first be modeled using a volumetric representation that characterizes the 3D object / region based on the 3D space occupied by the object, using, for example, multiple volume units such as voxels in the 3D space to represent it. The 3D object / region can include sub-parts, for example, the liver has multiple lobes, and each of the sub-parts can also be represented by some volume units included in the volumetric representation. That is, a subset of the volume units of the volume representation representing the sub-part of the 3D object. Each sub-part can be labeled differently so that the volume units belonging to different sub-parts have different labels. For example, each liver lobe can be given a different label.

[0035] A 3D object can also be characterized in terms of its surface, which can be modeled, for example, by a mesh representation. In some embodiments, such a mesh representation can include a plurality of surface units, each of which can model a corresponding patch of the object's surface, wherein each patch can have a corresponding sub-surface, which can be approximated as a plane and represented, for example, by a triangle, square, or rectangle. When modeled by geometric constructions (triangles, squares, or rectangles), each such planar sub-surface can include a plurality of vertices. For example, a sub-surface (or patch) can be approximately represented using a 2D triangle with three vertices or a rectangle with four vertices.

[0036] Region boundaries can be identified on the surface of an object. This may be particularly useful in the medical field. For example, an organ may include different anatomical parts (e.g., a liver has different lobes), but such anatomical parts may not be visually obvious from the surface of the organ. The present teaching discloses a solution for identifying region boundaries on the surface of an object, which separates adjacent sub-regions of a 3D object. In some embodiments, such region boundaries can be identified by assigning labels to the vertices of geometric units in a mesh representation based on the region labels assigned to different 3D regions connected to the vertices. If the vertices of a geometric unit such as a triangle are assigned different labels, this means that the triangle is located on a region boundary because it is connected to more than one sub-region of the 3D object. All geometric units identified in this way form a region boundary. The details of the present teaching will be discussed below with reference to different figures. Although the following disclosure uses a liver as an example of a 3D object to illustrate the relevant concepts, it is for illustrative purposes only and not for limiting purposes. The present teaching and related concepts can be applied to other types of objects.

[0037] Figure 1A A human liver 100 is shown, which typically has multiple lobes. Figure 1B As shown, the liver consists of two main lobes, one on each side. Each main lobe consists of eight lobes, namely 100-1, 100-2, ..., 100-7, and 100-8. Generally speaking, each lobe can be defined as a region with a relatively independent blood supply network. In some cases, a person may have a growth inside the liver, such as Figure 1C FIG. 1 shows a liver 100 in which a growth 110 is present. When such a growth is, for example, malignant, it may be necessary to remove it. Depending on how widespread the growth has been, it may be necessary to remove certain (one or more) areas of the liver. For example, if a cancerous growth has spread to two adjacent lobes, a liver resection procedure may be performed to remove both lobes. This is called a resection. Figure 1D This concept is illustrated visually, where the resected region 120 is a diseased area that may include multiple lobes.

[0038] As discussed herein, the present teachings utilize different representations of an object to identify region boundaries that separate adjacent regions of a 3D object. The different representations include, for example, a volumetric representation of the 3D object and a mesh representation of the surface of the 3D object. As discussed herein, representations of specific regions of a 3D object, such as a resected region of the liver, can also be obtained. Figure 1E An exemplary volume representation 130 of a 3D object is shown, comprising a plurality of volume units, each volume unit representing a unit area occupied by the object. Figure 1FAn exemplary mesh representation 140 for modeling the surface of a 3D object is shown. The mesh representation 140 may include a plurality of 2D connected geometric units, each having a shape and used to approximate patches on the surface of the object. In this example, each patch on the surface of the object is modeled using a triangle (geometric unit) having three vertices. As can be seen herein, a volume representation models a 3D object as a solid, while a mesh representation models the same 3D object based on its 3D surface.

[0039] Using the example of a human liver, a volumetric representation and a mesh representation of the liver can be derived. In some embodiments, its volumetric 3D representation can be obtained via 3D modeling based on, for example, image data. The lobes of the liver can be identified via segmentation based on, for example, the vascular network. Each segmented 3D lobe is formed by a plurality of voxels, which can be identified via labels. Voxels of adjacent lobes can be assigned different labels, such as Figure 1B . Segmentation of a 3D object including the liver and / or volume representation of the 3D object (or a portion thereof) may be obtained using any suitable existing technology or any technology developed in the future. A mesh representation of the liver or a portion thereof may also be derived by performing segmentation of the object by analyzing the image data to identify the surface of the liver. In some embodiments, the surface of the liver may also be derived based on a volume model of the liver. An example mesh representation 150 of the liver is shown in FIG. Figure 1G As shown in , a mesh representation is constructed using triangles to model the different patches on the liver surface.

[0040] As discussed herein, 3D volume models and surface mesh representations can also be used to represent a portion of a 3D object. For example, a resection region of a liver can be characterized based on a 3D volume model, and the surface of the resection region can also be characterized using a mesh representation (for the surface of the liver rather than for the interior of the liver due to resection). Therefore, the method for identifying region boundaries on the surface of the liver can also be applied to detect region boundaries on the surface of a portion of the liver (the resection region). During a partial hepatectomy, the resection region can be automatically or manually identified by the surgeon through interaction with a system that facilitates identification of the lobe to be removed. In this case, the resection region may also include multiple lobes, and it may be necessary to identify region boundaries from the surface of the resection region.

[0041] Figure 2AAn exemplary high-level system diagram of a framework 200 for identifying and displaying region / resection boundaries of an object according to an embodiment of the present teachings is depicted. In the illustrated embodiment, the framework 200 includes a 3D region volume modeling unit 210, a grid-based region boundary determiner 230, a registration unit 250, and a region boundary overlay display unit 260. The framework 200 identifies the region boundary on the surface of a designated 3D region (the entire liver or a portion thereof) and overlays the identified region boundary on a 2D display, so that the boundary of the liver on the surface is visualized for user operation.

[0042] The input to the framework 200 can be a 3D model of a liver or a resected portion of a liver with different lobe labels. Based on the input, the framework 200 identifies a 3D region / resection boundary on the surface of the liver and then projects the 3D region / resection boundary on the liver displayed on the 2D display as an overlay. The visualized liver on the 2D display can correspond to a 3D model rendered in 2D space from a certain perspective or a 2D liver image captured by a laparoscopic camera in order to monitor the position of a medical device inserted into the patient's body and the anatomical structure in front of the device. The identified region / resection boundary can be superimposed or overlaid on the displayed liver at a corresponding position determined based on a known perspective and alignment. The appropriately visualized resection boundary overlay enables a user (e.g., a surgeon) to see the resection boundary projected on the liver image so that the user can manipulate the surgical tool in a manner to remove the intended portion of the liver by following the resection boundary.

[0043] The 3D region volume modeling unit 210 is provided for obtaining a 3D volume model 220 of a 3D region (liver or resection region). In some embodiments, the 3D region to be modeled may include segmented liver lobes. In some embodiments, the 3D region volume model 220 may be generated based on image data provided as input by segmenting the liver from an image, and then further segmenting the different lobes based on, for example, the distribution of vascular networks identified from the image. In this case, the different lobes thus identified may be labeled with different labels. Such derived 3D region volume model 220 is then saved.

[0044] A grid-based region boundary determiner 230 is provided for identifying region boundaries. To this end, the grid-based region boundary determiner 230 generates a 3D mesh representation 240 to model the surface of the liver. As discussed herein, the mesh representation 240 includes a plurality of surface patches, each of which can be approximately represented by a 2D geometric unit having a specific shape. For example, a triangle can be used as a 2D geometric unit to model each surface patch. In this case, each triangle includes three vertices, and the surface of the liver can be represented by a mesh of connected triangles. Each vertex in the mesh representation is connected to a voxel in the 3D region volume model 220 for the liver. Since each voxel in the 3D region volume model 220 has a label indicating the lobe to which it belongs, each vertex in the mesh representation can also be labeled with the label of the voxel it is connected to. All vertices in the mesh representation 240 can be assigned labels accordingly. To identify region boundaries, triangles whose vertices have different labels are part of the region boundary of two adjacent lobes.

[0045] like Figure 3 , where an object 300 (e.g., a liver) has two exemplary regions 301 and 302, each labeled with a different label. According to the present teachings, a mesh-based representation of the object can be obtained, having connected triangles near the boundary dividing adjacent regions 301 and 302, e.g., triangles 321, 322, 323, 324, and 325. Each triangle has three vertices, and adjacent triangles share some of the vertices. For example, triangle 321 has vertices 311, 312, and 313, and vertices 312 and 313 are also vertices of triangle 325. According to the present teachings, when each vertex touches a voxel in a volumetric model of object 300, a label for labeling the vertex is determined based on the label of the voxel that the vertex touches. For example, vertex 312 of triangle 325 touches a voxel in region 301, such that the label of any voxel in region 301 is used to label vertex 312. Similarly, vertex 313 of triangle 325 has the same label as vertex 312 because vertex 313 also touches a voxel in region 301. However, when vertex 316 of triangle 325 touches a voxel in region 302, vertex 316 is labeled using the label of the voxel from region 302 to which it touches. That is, vertex 316 has a different label from vertices 312 and 313. Therefore, the three vertices of triangle 325 have different labels. Therefore, triangle 325 is identified as being located on the region boundary that divides adjacent regions 301 and 302. For the same reason, since the vertices of triangles 322 and 323 have different labels, they are also located on the region boundary that divides region 301 and region 302, as shown in FIG. Figure 3 As shown in .

[0046] The triangles thus identified form a region boundary. A region boundary overlay display unit 260 is provided to overlay the region boundary on the liver rendered on the 2D display. In some embodiments, the triangles in the region boundary are superimposed on the registered corresponding locations of the liver rendered on the 2D display. An example of such a display is shown in 270. As discussed herein, in some embodiments, the liver rendered on the 2D display may correspond to a 2D video image captured, for example, by a laparoscopic camera during a partial hepatectomy procedure. In this case, the region boundary represented by the plurality of triangles can be registered with the corresponding locations on the 2D video image by the registration unit 250. In some embodiments, the liver can be visualized by rendering a 3D model of the liver on a 2D display device. In this case, the region boundary is overlaid on the rendered 3D liver. In some embodiments, the 3D model of the liver can be rendered on the 2D display device in registration with the real-time 2D video image, such that the rendered liver has the same viewing angle as the camera that captured the 2D video image. In this case, the region boundary can then be registered with the rendered 3D liver, so that the triangles in the boundary can be superimposed on the registered corresponding locations.

[0047] Figure 2B 2 is a flow chart of an exemplary process for a framework 200 for identifying and rendering region boundaries of an object (liver or resection region) according to an embodiment of the present teachings. Input is first received at 205. In some embodiments, the input may correspond to a 3D model of the object having segmented regions with labels. In some embodiments, the input may correspond to image data from which the object and the regions included therein may be identified and labeled. Based on the input, a 3D region volume modeling unit 210 may obtain a 3D region volume model 220 at 215. As discussed herein, the 3D region volume model 220 represents the object in terms of the 3D space it occupies, represented by a plurality of voxels in the 3D space. Voxels in different segmented regions (e.g., lobes) are assigned different labels. At 225, a mesh-based region boundary determiner 230 may generate a 3D surface mesh representation 240 to represent the surface of the object. The surface mesh representation 240 may be derived based on the input image data, the 3D model of the object, or the generated 3D region volume model 220. As discussed herein, the mesh-based representation may be constructed to include a plurality of connected geometric units, such as triangles.

[0048] Based on the 3D region volume model 220 and the mesh-based surface representation 240, the mesh-based region boundary determiner 230 identifies the region boundary based on the triangles with vertices having different labels in the mesh-based surface representation 240 at 235. To display the identified resection boundary on the 2D display, the registration unit 250 performs the required registration at 245, and the region boundary overlay display unit 260 displays the registered region boundary on the 2D display device at 255, for example, marking different regions (leaves) with different labels.

[0049] Figure 4A An exemplary high-level system diagram of a mesh-based region boundary determiner 230 according to an embodiment of the present teachings is depicted. As discussed herein, the mesh-based region boundary determiner 230 identifies boundaries between adjacent regions of an object. In the illustrated embodiment, the mesh-based region boundary determiner 230 includes a 3D surface mesh representation generator 310, a region label-based vertex labeling unit 320, and a mesh cell-based boundary identifier 340.

[0050] Figure 4B is a flow chart of an exemplary process of the mesh-based region boundary determiner 230 according to an embodiment of the present teachings. In operation, the 3D surface mesh representation generator 310 receives input for generating a mesh representation for modeling the surface of a 3D object at 405. After receiving the input, the mesh representation is generated at 415. In some embodiments, the 3D surface mesh representation 240 can be obtained based on a 3D model of the object. In some embodiments, the 3D resection region volume model 220 can also be used to obtain the 3D surface mesh representation.

[0051] As discussed herein, the 3D surface mesh representation 240 can be constructed to include a plurality of mesh cells, each of which can correspond to a geometric shape such as a triangle or rectangle having a plurality of vertices. At 425, the region label-based vertex labeling unit 320 is called to label each of the vertices in the 3D surface mesh representation. Specifically, for each of the vertices, the label assigned to the adjacent voxel in the 3D region volume model 220 is used to label the vertex. Once all vertices are labeled, the grid cell-based boundary identifier 340 operates to identify, at 435, grid cells (or triangles, in this example) that have different labels on their vertices. Then, at 445, such identified grid cells are classified as region boundaries. Then, at 455, the grid cell-based boundary identifier 340 outputs such identified region boundaries.

[0052] Figure 5A visualization of a 3D liver with an abnormal growth is shown with overlaid resection region boundaries in accordance with an embodiment of the present teachings. In this example, the resection region includes multiple lobes surrounding the abnormal growth, and the region boundaries of these lobes identified in accordance with the present teachings are visualized. This visualization provides the user with a focused view of the resection boundaries without diverting the user's attention to areas that are not part of the resection. In some embodiments, region boundaries of other areas not affected by the procedure may also be visualized. When all region boundaries are visualized, appropriate visual markers may be applied to highlight the resection region and associated region boundaries. In some embodiments, any portion of the resection region may be magnified to show more detail. This may further assist the user in having a close-up view of the details of important areas. Figure 6 A close-up view of a specific portion of the resected area near the abnormal growth is shown.

[0053] Figure 7 is a schematic diagram of an exemplary mobile device architecture that may be used to implement a dedicated system for implementing the present teachings in accordance with various embodiments. In this example, the user device on which the present teachings may be implemented corresponds to a mobile device 700, including but not limited to a smartphone, a tablet computer, a music player, a handheld game console, a global positioning system (GPS) receiver, and a wearable computing device, or in any other form factor. The mobile device 700 may include one or more central processing units ("CPUs") 740, one or more graphics processing units ("GPUs") 730, a display 720, a memory 760, a communication platform 710 (such as a wireless communication module), a storage device 790, and one or more input / output (I / O) devices 750. Any other suitable components, including but not limited to a system bus or controller (not shown), may also be included in the mobile device 700. As Figure 7 As shown, a mobile operating system 770 (e.g., iOS, Android, Windows Phone, etc.) and one or more applications 780 can be loaded from storage 790 into memory 760 for execution by CPU 740. Application 780 can include, at least in part, a user interface for analyzing and managing information according to the present teachings on mobile device 700, or any other suitable mobile application. User interaction, if any, can be implemented via device 750 and provided to various components connected via network(s).

[0054] In order to realize each module, unit and function thereof described in the present disclosure, computer hardware platform can be used as (one or more) hardware platform of one or more elements described herein.The hardware components, operating system and programming language of this type of computer are conventional in nature, and it is assumed that those skilled in the art are fully familiar with to adapt these technologies to the appropriate settings described herein.The computer with user interface element can be used to realize personal computer (PC) or other types of workstations or terminal equipment, although if suitably programmed, computer also can serve as server.It is believed that those skilled in the art are familiar with the structure, programming and general operation of this type of computer equipment, so accompanying drawing should be self-explanatory.

[0055] Figure 8 800 is a schematic diagram of an exemplary computing device architecture that can be used to implement a dedicated system for implementing the present teachings according to various embodiments. Such a dedicated system in conjunction with the present teachings has a functional block diagram of a hardware platform including user interface elements. The computer can be a general-purpose computer or a special-purpose computer. Both can be used to implement a dedicated system for the present teachings. The computer 800 can be used to implement any component or aspect of the framework disclosed herein. For example, the information analysis and management methods and systems disclosed herein can be implemented on a computer such as computer 800 via the computer's hardware, software programs, firmware, or a combination thereof. Although only one such computer is shown for convenience, the computer functions described herein in connection with the present teachings can be implemented in a distributed manner on several similar platforms to distribute the processing load.

[0056] The computer 800 includes, for example, a COM port 850 that is connected to and from a network connected to the COM port 850 to facilitate data communications. The computer 800 also includes a central processing unit (CPU) 820 in the form of one or more processors for executing program instructions. The exemplary computer platform includes an internal communication bus 810, various forms of program storage and data storage (e.g., disk 870, read-only memory (ROM) 830, or random access memory (RAM) 840) for various data files to be processed and / or transferred by the computer 800 and possible program instructions to be executed by the CPU 820. The computer 800 also includes an I / O component 860 that supports input / output flows between the computer and other components in the computer (such as user interface elements 880). The computer 800 can also receive programming and data via network communications.

[0057] Thus, as described above, aspects of the information analysis and management methods and / or other processes may be embodied in programming. The programmatic aspects of the technology may be considered to be a "product" or "article of manufacture" typically in the form of executable code and / or associated data executed on or implemented in some type of machine-readable medium. Tangible, non-transitory "storage" type media include any or all of memory or other storage for a computer, processor, or the like, or its associated modules (such as various semiconductor memories, tape drives, disk drives, etc.) that may provide storage for software programming at any time.

[0058] All or part of the software may sometimes be delivered over a network, such as the Internet or various other telecommunication networks. Such communications, for example, may enable software to be loaded from one computer or processor to another, for example, in connection with information analysis and management. Thus, another type of medium that may carry software elements includes optical, electrical, and electromagnetic waves, such as used across physical interfaces between local devices, through wired and optical ground networks, and through various air links. Physical elements that carry such waves, such as wired or wireless links, optical links, or the like, may also be considered to be the medium that carries the software. As used herein, unless limited to tangible "storage" media, terms such as computer or machine "readable media" refer to any medium that participates in providing instructions to a processor for execution.

[0059] Thus, a machine-readable medium can take many forms, including but not limited to tangible storage media, carrier media, or physical transmission media. Non-volatile storage media include, for example, optical or magnetic disks that can be used to implement the system shown in the accompanying drawings or any of the components of the system, such as any of the storage devices or the like in any (one or more) computers. Volatile storage media include dynamic memory, such as the main memory of such a computer platform. Tangible transmission media include coaxial cables; copper wire and optical fiber, including the wires that form a bus within a computer system. Carrier transmission media can take the form of electrical or electromagnetic signals, or acoustic or light waves, such as those generated during radio frequency (RF) and infrared (IR) data communications. Thus, common forms of computer-readable media include, for example, a floppy disk, a flexible disk, a hard disk, magnetic tape, any other magnetic medium, a CD-ROM, a DVD or DVD-ROM, any other optical medium, punched card stock tape, any other physical storage medium with a pattern of holes, RAM, PROM and EPROM, FLASH-EPROM, any other memory chip or cassette, a carrier wave that transports data or instructions, a cable or link that transports such a carrier wave, or any other medium from which a computer can read programming code and / or data. Many of these forms of computer-readable media may be involved in carrying one or more sequences of one or more instructions to a physical processor for execution.

[0060] Those skilled in the art will recognize that the teachings herein are amenable to various modifications and / or enhancements. For example, while the implementation of the various components described above may be embodied in a hardware device, it may also be implemented as a software-only solution, for example, installed on an existing server. Additionally, the technology disclosed herein may be implemented as firmware, a firmware / software combination, a firmware / hardware combination, or a hardware / firmware / software combination.

[0061] Although the foregoing has described what is considered to constitute the present teachings and / or other examples, it should be understood that various modifications may be made thereto, and the subject matter disclosed herein may be implemented in various forms and examples, and the teachings may be applied to many applications, only some of which have been described herein. It is intended that the appended claims claim any and all applications, modifications, and variations that fall within the true scope of the present teachings.

Claims

1. A method implemented on at least one processor, memory, and communication platform, the method comprising: receiving input associated with a three-dimensional (3D) object including a plurality of regions; Acquire a 3D volume model representing the 3D object, wherein the 3D object includes a plurality of regions, each region occupies a plurality of voxels in the 3D volume model, and voxels in each of the plurality of regions have the same label; generating a 3D surface mesh representation representing a surface of the 3D object, wherein the 3D surface mesh representation comprises a plurality of connected geometric cells; identifying region boundaries on a surface of the 3D object based on the 3D surface mesh representation and the 3D volume model; Rendering the 3D object on a two-dimensional (2D) display device; as well as Overlaying the region boundary of the 3D object on the rendered 3D object.

2. The method according to claim 1, characterized in that The 3D object corresponds to a human liver or a resected region of the human liver; and The plurality of regions correspond to leaves of the 3D object; and The resection region is defined based on abnormal growth detected within the human liver.

3. The method according to claim 1, characterized in that Voxels in different regions of the 3D object are assigned different labels.

4. The method according to claim 3, characterized in that Each of the geometric units has a geometric shape corresponding to one of a triangle, a rectangle, and a square; and Each of the geometric units is defined by a plurality of vertices.

5. The method according to claim 4, characterized in that Marking area boundaries includes: determining, for each vertex of each of the geometric cells, a vertex label based on a voxel label assigned to a voxel from the 3D volume model, wherein the vertex touches the voxel; and The voxel labels are assigned to the vertices.

6. The method according to claim 5, further comprising: designating each of the geometric cells of the 3D surface mesh representation having vertices with different vertex labels as a region boundary cell; as well as The region boundary is generated on the surface of the 3D object based on the region boundary unit.

7. The method according to claim 1, characterized in that Covering the area boundaries includes: determining a viewing angle for rendering the 3D object on the 2D display device; registering the region boundary on the surface of the 3D object based on the viewing angle; and Each of the geometric units in the region boundary is projected onto the 2D display device based on the registration result.

8. A machine-readable medium having information recorded thereon, characterized in that: The medium, when read by the machine, causes the machine to perform the following steps: receiving input associated with a three-dimensional (3D) object including a plurality of regions; Acquire a 3D volume model representing the 3D object, wherein the 3D object comprises a plurality of regions, each region occupies a plurality of voxels in the 3D volume model, and the voxels in each of the plurality of regions have the same label; generating a 3D surface mesh representation representing a surface of the 3D object, wherein the 3D surface mesh representation comprises a plurality of connected geometric cells; identifying region boundaries on a surface of the 3D object based on the 3D surface mesh representation and the 3D volume model; Rendering the 3D object on a two-dimensional (2D) display device; as well as Overlaying the region boundary of the 3D object on the rendered 3D object.

9. The medium according to claim 8, characterized in that The 3D object corresponds to a human liver or a resected region of the human liver; and The plurality of regions correspond to leaves of the 3D object; and The resection region is defined based on abnormal growth detected within the human liver.

10. The medium according to claim 8, characterized in that Voxels in different regions of the 3D object are assigned different labels.

11. The medium according to claim 10, characterized in that Each of the geometric units has a geometric shape corresponding to one of a triangle, a rectangle, and a square; and Each of the geometric units is defined by a plurality of vertices.

12. The medium according to claim 11, characterized in that Marking area boundaries includes: determining, for each vertex of each of the geometric cells, a vertex label based on a voxel label assigned to a voxel from the 3D volume model, wherein the vertex touches the voxel; and The voxel labels are assigned to the vertices.

13. The medium according to claim 12, characterized in that When the information is read by the machine, it also causes the machine to execute: designating each of the geometric cells of the 3D surface mesh representation having vertices with different vertex labels as a region boundary cell; and The region boundary is generated on the surface of the 3D object based on the region boundary unit.

14. The medium according to claim 8, characterized in that Covering the area boundaries includes: determining a viewing angle for rendering the 3D object on the 2D display device; registering the region boundary on the surface of the 3D object based on the viewing angle; and Each of the geometric units in the region boundary is projected onto a 2D display device based on the registration result.

15. A system comprising: A 3D region volume modeling unit implemented by a processor, and configured to: receiving input associated with a three-dimensional (3D) object including a plurality of regions therein; and Acquire a 3D volume model representing the 3D object, wherein the 3D object comprises a plurality of regions, each region occupies a plurality of voxels in the 3D volume model, and the voxels in each of the plurality of regions have the same label; A grid-based region boundary determiner implemented by a processor and configured to generating a 3D surface mesh representation representing a surface of the 3D object, wherein the 3D surface mesh representation comprises a plurality of connected geometric cells; as well as identifying region boundaries on a surface of the 3D object based on the 3D surface mesh representation and the 3D volume model; as well as The area boundary covering display unit implemented by the processor is configured to Rendering the 3D object on a two-dimensional (2D) display device, and Overlaying the region boundary of the 3D object on the rendered 3D object.

16. The system according to claim 15, characterized in that The 3D object corresponds to a human liver or a resected region of the human liver; and The plurality of regions correspond to leaves of the 3D object; and The resection region is defined based on abnormal growth detected within the human liver.

17. The system according to claim 15, wherein: Voxels in different regions of the 3D object are assigned different labels.

18. The system according to claim 17, characterized in that Each of the geometric units has a geometric shape corresponding to one of a triangle, a rectangle, and a square; and Each of the geometric units is defined by a plurality of vertices.

19. The system according to claim 18, wherein: The grid-based region boundary determiner comprises: A vertex labeling unit based on region labels is implemented by a processor, and the vertex labeling unit based on region labels is configured to determining, for each vertex of each of the geometric units, a vertex label based on a voxel label assigned to a voxel from the 3D volume model to which the vertex touches, and The voxel labels are assigned to the vertices.

20. The system according to claim 19, wherein: The grid-based region boundary determiner further comprises: A grid cell based boundary marker implemented by a processor and configured to designating each of the geometric cells of the 3D surface mesh representation having vertices with different vertex labels as a region boundary cell, and The region boundary is generated on the surface of the 3D object based on the region boundary unit.

21. The system according to claim 15, wherein: The region boundary covering display unit covers the region edge in the following manner: determining a viewing angle for rendering the 3D object on the 2D display device; registering the region boundary on the surface of the 3D object based on the viewing angle; as well as Each of the geometric units in the region boundary is projected onto a 2D display device based on the registration result.

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