A high-resolution model for soft tissue deformation based on point primitives. (September 2017)

• Record Type: Journal Article
• Authors: Zou, Yanni; Liu, Peter X.
• Is Part Of: Computer methods and programs in biomedicine. Volume 148(2017)
• Page Start: 113
• Page End: 121
• Publication Date: 2017-09
• Subjects: Point primitive -- Deformable model -- High resolution -- Physical properties -- Volumetric data; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2017.06.013
• Languages: English
• ISSNs: 0169-2607

Abstract

Highlights: A high-resolution model for soft tissue deformation based on point primitives is proposed. Octree data structure is used to record the topology relationship in this model. The high-resolution model has been implemented into the development of a neurosurgery simulator. The visual effects and computation cost of the proposed model are evaluated and compared with conventional primitives-based methods. Abstract: Background and objectives : In order to achieve a high degree of visual realism in surgery simulation, we propose a new model, which is based on point primitives and continuous elastic mechanics theory, for soft tissue deformation, tearing and/or cutting. Methods : The model can be described as a two-step local high-resolution strategy. First, appropriate volumetric data are sampled and assigned with proper physical properties. Second, sparsely sampled points in non-deformed regions and densely-sampled points in the deformed zone are selected and evaluated. By using a meshless deformation model based on point primitives for all volumetric data, the affine transform matrix of collision points can be computed. The new positions of neighboring points in the collided surface can be then calculated, and more details in the local deformed zone can be obtained for rendering. Technical details about the derivations of the proposed model as well as its implementation are given. Results : The visual effects and computation cost of the proposed model are evaluated and compared with conventional primitives-based methods. Experimental results show that the proposed model provides users (trainees) with improved visual feedback while the computational cost is at the same magnitude of other similar methods. Conclusions : The proposed method is especially suitable for the simulation of soft tissue deformation and tearing because no grid information needs to be maintained. It can simulate soft tissue deformation in a high degree of authenticity with real-time performance. It could be considered implemented in the development of a mixed reality application of neurosurgery simulators in the future.