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001 9910484835303321
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010   $a3-030-15585-4
024 7 $a10.1007/978-3-030-15585-8
035   $a(CKB)4100000007881280
035   $a(DE-He213)978-3-030-15585-8
035   $a(MiAaPQ)EBC5927995
035   $z(PPN)258849940
035   $a(PPN)243769210
035   $a(EXLCZ)994100000007881280
100   $a20190406d2019      u|         0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aReal-time Knowledge-based Fuzzy Logic Model for Soft Tissue Deformation /$fby Joey Sing Yee Tan, Amandeep S. Sidhu
205   $a1st ed. 2019.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019.
215   $a1 online resource (IX, 88 p.) 
225 1 $aData, Semantics and Cloud Computing,$x2524-6593 ;$v832
311   $a3-030-15584-6 
320   $aIncludes bibliographical references.
327   $aList of Figures -- List of Tables -- Chapter 1. Introduction -- Chapter 2. Background -- Chapter 3. Methodology -- Chapter 4. Fuzzy Inference System, etc.
330   $aThis book provides a real-time and knowledge-based fuzzy logic model for soft tissue deformation. The demand for surgical simulation continues to grow, as there is a major bottleneck in surgical simulation designation and every patient is unique. Deformable models, the core of surgical simulation, play a crucial role in surgical simulation designation. Accordingly, this book (1) presents an improved mass spring model to simulate soft tissue deformation for surgery simulation; (2) ensures the accuracy of simulation by redesigning the underlying Mass Spring Model (MSM) for liver deformation, using three different fuzzy knowledge-based approaches to determine the parameters of the MSM; (3) demonstrates how data in Central Processing Unit (CPU) memory can be structured to allow coalescing according to a set of Graphical Processing Unit (GPU)-dependent alignment rules; and (4) implements heterogeneous parallel programming for the distribution of grid threats for Computer Unified Device Architecture (CUDA)-based GPU computing. .
410  0$aData, Semantics and Cloud Computing,$x2524-6593 ;$v832
606   $aComputational intelligence
606   $aBiomedical engineering
606   $aSurgery
606   $aRegenerative medicine
606   $aTissue engineering
606   $aComputational Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/T11014
606   $aBiomedical Engineering and Bioengineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T2700X
606   $aSurgery$3https://scigraph.springernature.com/ontologies/product-market-codes/H59001
606   $aRegenerative Medicine/Tissue Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/L16080
615  0$aComputational intelligence.
615  0$aBiomedical engineering.
615  0$aSurgery.
615  0$aRegenerative medicine.
615  0$aTissue engineering.
615 14$aComputational Intelligence.
615 24$aBiomedical Engineering and Bioengineering.
615 24$aSurgery.
615 24$aRegenerative Medicine/Tissue Engineering.
676   $a511.313
676   $a511.313
700   $aTan$b Joey Sing Yee$4aut$4http://id.loc.gov/vocabulary/relators/aut$01227329
702   $aSidhu$b Amandeep S$4aut$4http://id.loc.gov/vocabulary/relators/aut
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910484835303321
996   $aReal-time Knowledge-based Fuzzy Logic Model for Soft Tissue Deformation$92849847
997   $aUNINA