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Real-time Knowledge-based Fuzzy Logic Model for Soft Tissue Deformation
Details
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.
Presents an improved mass spring model to simulate soft tissue deformation The first specific contribution on liver modeling using a real-time and knowledge-based fuzzy mass spring model Provides a real-time and knowledge-based fuzzy logic model for soft tissue deformation
Inhalt
List of Figures.- List of Tables.- Chapter 1. Introduction.- Chapter 2. Background.- Chapter 3. Methodology.- Chapter 4. Fuzzy Inference System, etc.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783030155841
- Auflage 1st edition 2019
- Sprache Englisch
- Genre Allgemeines & Lexika
- Lesemotiv Verstehen
- Größe H241mm x B160mm x T12mm
- Jahr 2019
- EAN 9783030155841
- Format Fester Einband
- ISBN 3030155846
- Veröffentlichung 19.04.2019
- Titel Real-time Knowledge-based Fuzzy Logic Model for Soft Tissue Deformation
- Autor Amandeep S. Sidhu , Joey Sing Yee Tan
- Untertitel Studies in Computational Intelligence 832 - Data, Semantics and Cloud Computing
- Gewicht 325g
- Herausgeber Springer International Publishing
- Anzahl Seiten 100