1.

Record Nr.

UNINA9910484835303321

Autore

Tan Joey Sing Yee

Titolo

Real-time Knowledge-based Fuzzy Logic Model for Soft Tissue Deformation [[electronic resource] /] / by Joey Sing Yee Tan, Amandeep S. Sidhu

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019

ISBN

3-030-15585-4

Edizione

[1st ed. 2019.]

Descrizione fisica

1 online resource (IX, 88 p.)

Collana

Data, Semantics and Cloud Computing, , 2524-6593 ; ; 832

Disciplina

511.313

Soggetti

Computational intelligence

Biomedical engineering

Surgery

Regenerative medicine

Tissue engineering

Computational Intelligence

Biomedical Engineering and Bioengineering

Regenerative Medicine/Tissue Engineering

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references.

Nota di contenuto

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

Sommario/riassunto

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. .