Real-time Knowledge-based Fuzzy Logic Model for Soft Tissue Deformation

• Main Authors: Tan, Joey Sing Yee (Author, http://id.loc.gov/vocabulary/relators/aut), Sidhu, Amandeep S. (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Series: Data, Semantics and Cloud Computing, 832
• Subjects: Computational intelligence.; Biomedical engineering.; Surgery.; Regenerative medicine.; Tissue engineering.; Computational Intelligence.; Biomedical Engineering and Bioengineering.; Regenerative Medicine/Tissue Engineering.

 This book provides a real-time and knowledge-based fuzzy logic model for soft tissue deformation. The demand for surgical simulation continues to grow, as there is a major bottleneck in surgical simulation designation and every patient is unique. Deformable models, the core of surgical simulation, play a crucial role in surgical simulation designation. Accordingly, this book (1) presents an improved mass spring model to simulate soft tissue deformation for surgery simulation; (2) ensures the accuracy of simulation by redesigning the underlying Mass Spring Model (MSM) for liver deformation, using three different fuzzy knowledge-based approaches to determine the parameters of the MSM; (3) demonstrates how data in Central Processing Unit (CPU) memory can be structured to allow coalescing according to a set of Graphical Processing Unit (GPU)-dependent alignment rules; and (4) implements heterogeneous parallel programming for the distribution of grid threats for Computer Unified Device Architecture (CUDA)-based GPU computing. . 

 List of Figures -- List of Tables -- Chapter 1. Introduction -- Chapter 2. Background -- Chapter 3. Methodology -- Chapter 4. Fuzzy Inference System, etc.