System and method for processing colon image data

Abstract

Systems and methods for processing colon image data are provided. Image data related to a first ROI may be obtained, wherein the first ROI may include a soft tissue represented by a plurality of voxels, and each voxel may have a voxel value. A first virtual scene may be visualized based on the image data, wherein the first virtual scene may reveal at least one portion of the first ROI. A collision detection may be performed between at least one portion of the first ROI and a virtual object in the first virtual scene. A feedback force may be determined from at least one portion of the first ROI based on the collision detection. At least one of the plurality of voxels corresponding to a second ROI may be determined based on the feedback force, wherein the second ROI may relate to the soft tissue in the first ROI.

1 - 24 . (canceled) 
     
     
         25 . A method implemented on a computing device having at least one processor and a storage medium, the method comprising:
 obtaining image data related to a first ROI, the first ROI including a soft tissue represented by a plurality of voxels, each of the plurality of voxels having a voxel value;   determining a soft tissue model based on one or more biomechanical properties of the soft tissue and the image data, the biomechanical properties including at least one of elasticity or viscoelasticity;   determining a feedback force from at least one portion of the first ROI based on the soft tissue model and a collision detection; and   identifying a second ROI from the first ROI based on the feedback force and a relationship model between feedback forces and characteristic information of different objects, the second ROI being related to the soft tissue in the first ROI.   
     
     
         26 . The method of  claim 25 , wherein the soft tissue model includes an integration of a geometric model and a physical model,
 the geometric model includes a plurality of meshes and the plurality of meshes includes a plurality of nodes,   one or more nodes are defined as one or more mass points of the physical model, and   two or more adjacent mass points are connected by one or more springs to form the physical model.   
     
     
         27 . The method of  claim 25 , wherein performing the collision detection comprises:
 visualizing a first virtual scene based on the image data and the soft tissue model, the first virtual scene revealing at least one portion of the first ROI; and   performing the collision detection between the at least one portion of the first ROI and a virtual object in the first virtual scene.   
     
     
         28 . The method of  claim 27 , wherein the performing the collision detection between the at least one portion of the first ROI and the virtual object in the first virtual scene comprises:
 obtaining collision information including one or more parameters with respect to a pressure; and   performing the collision detection by imposing the pressure on the at least one portion of the first ROI via the virtual object.   
     
     
         29 . The method of  claim 28 , wherein the one or more parameters include at least one of a value of the pressure, a direction of the pressure, a speed for applying the pressure, or a position for bearing the pressure. 
     
     
         30 . The method of  claim 27 , wherein the determining the feedback force from the at least one portion of the first ROI based on the soft tissue model and the collision detection comprises:
 determining one or more collision parameters based on the collision detection, the collision parameters including at least one of a direction of the collision, a force of the collision, a speed of the collision, or a position of the collision; and   determining the feedback force based on the soft tissue model and the one or more collision parameters.   
     
     
         31 . The method of  claim 27 , wherein the determining the feedback force from the at least one portion of the first ROI based on the soft tissue model and the collision detection comprises:
 determining a press depth of the at least one portion of the first ROI induced by the virtual object based on the soft tissue model; and   determining the feedback force based on the press depth.   
     
     
         32 . The method of  claim 31 , further comprising:
 determining a deformation of the at least one portion of the first ROI based on the press depth and the soft tissue model;   updating at least one of the plurality of nodes of the soft tissue model; and   rendering a second virtual scene based on the updated plurality of nodes, the second virtual scene revealing the at least one portion of the first ROI with deformation.   
     
     
         33 . The method of  claim 32 , further comprising:
 revisualizing the first virtual scene upon releasing the collision between the at least one portion of the first ROI and the virtual object.   
     
     
         34 . The method of  claim 25 , further comprising:
 causing a virtual reality device to convert the feedback force to a sensation signal, the sensation signal assisting a user to determine whether the soft tissue is an abnormal tissue.   
     
     
         35 . The method of  claim 27 , further comprising:
 obtaining user interaction information associated with the first virtual scene from an interaction device; and   rendering a third virtual scene based on the user interaction information and the image data.   
     
     
         36 . The method of  claim 35 , wherein the obtaining the user interaction information associated with the first virtual scene from the interaction device comprises:
 extracting a center line of the at least one portion of the first ROI in the image data based on the soft tissue model; and   acquiring the user interaction information based on the center line.   
     
     
         37 . The method of  claim 25 , wherein the first ROI includes a colon, and the second ROI includes one and more polypuses. 
     
     
         38 . A method implemented on a computing device having at least one processor and a storage medium, the method comprising:
 obtaining image data related to an ROI;   building a first virtual scene based on the image data, the first virtual scene revealing at least one portion of the ROI;   acquiring user interaction information associated with the first virtual scene from an interaction device; and   controlling a position of a virtual camera in the first virtual scene based on the user interaction information, a region closer to the virtual camera being represented in the first virtual scene with a high resolution, and a region far from the first virtual camera being represented with a low resolution.   
     
     
         39 . The method of  claim 38 , wherein building the first virtual scene based on the image data comprises:
 determining a first model, the first model including structure information for reconstructing the ROI based on the image data; and   rendering the first virtual scene based on the first model and the image data.   
     
     
         40 . The method of  claim 39 , wherein the first model includes an integration of a geometric model and a physical model,
 the geometric model includes a plurality of meshes and the plurality of meshes includes a series of nodes,   one or more nodes are defined as one or more mass points of the physical model, and   two or more adjacent mass points are connected by one or more springs to form the physical model.   
     
     
         41 . The method of  claim 39 , wherein the acquiring the user interaction information associated with the first virtual scene from the interaction device comprises:
 extracting a center line of the ROI in the image data based on the first model; and   acquiring the user interaction information based on the center line.   
     
     
         42 . The method of  claim 38 , further comprising:
 updating the first virtual scene based on the position of the virtual camera.   
     
     
         43 . The method of  claim 42 , wherein the ROI includes a colon represented by a plurality of voxels, the method further comprises:
 determining a polypus based on the updated virtual scene.   
     
     
         44 . A system, comprising:
 at least one storage medium storing a set of instructions; and   at least one processor in communication with the at least one storage medium, wherein when executing the set of instructions, the at least one processor is configured to cause the system to:
 obtain image data related to a first ROI, the first ROI including a soft tissue represented by a plurality of voxels, each of the plurality of voxels having a voxel value; 
 determine a soft tissue model based on biomechanical properties of the soft tissue and the image data, the biomechanical properties including at least one of elasticity or viscoelasticity; 
 determine a feedback force from the at least one portion of the first ROI based on the soft tissue model and a collision detection; and 
 identify a second ROI from the first ROI based on the feedback force and a relationship model between feedback forces and characteristic information of different objects, the second ROI being related to the soft tissue in the first ROI.