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GPU-based automatic generation and collision detection method for soft tissue organ metaball model

A technology of collision detection and automatic generation, which is applied in the direction of instruments, 3D modeling, image data processing, etc., can solve the problem of insufficient real speed of traditional methods, and achieve the effect of simple calculation of intersection, high real-time performance, and fewer balls

Active Publication Date: 2016-01-20
BEIHANG UNIV
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Problems solved by technology

[0005] The technical problem solved by the present invention is: aiming at the problem that the traditional method in virtual surgery is not realistic enough or the speed is too slow, it provides a metaball model generation algorithm of soft tissue organs, and uses the metaball model to deal with the model collision problem

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  • GPU-based automatic generation and collision detection method for soft tissue organ metaball model
  • GPU-based automatic generation and collision detection method for soft tissue organ metaball model
  • GPU-based automatic generation and collision detection method for soft tissue organ metaball model

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Embodiment Construction

[0032] figure 1 The processing flow of the method for automatic generation and collision detection of soft tissue organ metaball models based on GPU is given, and the present invention is further described below in conjunction with other drawings and specific implementation methods.

[0033] The present invention provides a method for automatic generation and collision detection of soft tissue organ metaball models based on GPU. The main steps are introduced as follows:

[0034] 1. Generate the initial metaball model

[0035] This method generates an initial metaball model from an input triangle mesh. The initial input is a triangular mesh model file, stored in obj format, such as figure 2 shown. For triangular mesh models, point sampling is performed on it. The number of sampling points can be set manually, and different numbers represent the density of sampling points. Traverse each triangle of the triangle mesh and place the triangle vertices in the initial set of sam...

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Abstract

The invention provides a GPU-based automatic generation and collision detection method for a soft tissue organ metaball model. The method comprises four steps: a metaball model generation step: performing point sampling of an original mesh, calculating a Voronoi diagram of a mesh model, acquiring a medial surface of a triangular mesh model, and placing an initial ball on the medial surface; a step for local optimization of the metaball model: according to the initial position and radius of the metaball model, utilizing the method for adjusting the radius, the method of filling and other methods to perform local optimization of the metaball model; a step for global optimization of the metaball model: utilizing a charge gravity model, and calculating the gravity between the metaball and the gap to move and adjust the position of the metaball; and a collision detection step: utilized the generated metaball model to perform collision among soft tissue organs and collision between soft tissues and surgical instruments. The invention provides a soft tissue modeling method and a collision detection method for a virtual surgery. The soft tissue modeling method and the collision detection method for a virtual surgery can use a GPU parallel computation to realize acceleration and are high in real-time.

Description

technical field [0001] The invention relates to a simulation method for automatic generation and collision detection of metaball models of soft tissue organs in virtual surgery based on GPU parallel computing. Background technique [0002] With the improvement of computer hardware processing performance, surgical simulators based on virtual reality technology have been extensively studied. Model building and collision detection are the key technologies in virtual surgery. The establishment of the soft tissue model and collision detection mainly include three aspects: the first is to generate the initial metaball model based on the triangular mesh model; the second is to optimize the initial metaball model locally and globally; The model performs systematic collision detection. When designing the modeling algorithm, the above three issues should be considered at the same time to ensure that the system has better real-time and authenticity. [0003] Collision detection is a...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T17/30
Inventor 潘俊君赵成凯郝爱民秦洪
Owner BEIHANG UNIV
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