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Record Nr. |
UNINA9910484835303321 |
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Autore |
Tan Joey Sing Yee |
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Titolo |
Real-time Knowledge-based Fuzzy Logic Model for Soft Tissue Deformation [[electronic resource] /] / by Joey Sing Yee Tan, Amandeep S. Sidhu |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
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ISBN |
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Edizione |
[1st ed. 2019.] |
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Descrizione fisica |
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1 online resource (IX, 88 p.) |
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Collana |
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Data, Semantics and Cloud Computing, , 2524-6593 ; ; 832 |
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Disciplina |
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Soggetti |
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Computational intelligence |
Biomedical engineering |
Surgery |
Regenerative medicine |
Tissue engineering |
Computational Intelligence |
Biomedical Engineering and Bioengineering |
Regenerative Medicine/Tissue Engineering |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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List of Figures -- List of Tables -- Chapter 1. Introduction -- Chapter 2. Background -- Chapter 3. Methodology -- Chapter 4. Fuzzy Inference System, etc. |
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Sommario/riassunto |
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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 |
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