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Biomedical Image Analysis - Pritpal Singh - Bog

Bag om Biomedical Image Analysis

This book provides an in-depth study of biomedical image analysis. It reviews and summarizes previous research work in biomedical image analysis and also provides a brief introduction to other computation techniques, such as fuzzy sets, neutrosophic sets, clustering algorithm and fast forward quantum optimization algorithm, focusing on how these techniques can be integrated into different phases of the biomedical image analysis. In particular, this book describes novel methods resulting from the fuzzy sets, neutrosophic sets, clustering algorithm and fast forward quantum optimization algorithm. It also demonstrates how a new quantum-clustering based model can be successfully applied in the context of clustering the COVID-19 CT scans. Thanks to its easy-to-read style and the clear explanations of the models, the book can be used as a concise yet comprehensive reference guide to biomedical image analysis, and will be valuable not only for graduate students, but also forresearchers and professionals working for academic, business and government institutes and medical colleges.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9789819999385
  • Indbinding:
  • Hardback
  • Sideantal:
  • 180
  • Udgivet:
  • 31. Marts 2024
  • Udgave:
  • 24001
  • Størrelse:
  • 160x16x241 mm.
  • Vægt:
  • 442 g.
  • 2-4 uger.
  • 11. Juni 2024
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Beskrivelse af Biomedical Image Analysis

This book provides an in-depth study of biomedical image analysis. It
reviews and summarizes previous research work in biomedical image analysis and
also provides a brief introduction to other computation techniques, such as
fuzzy sets, neutrosophic sets, clustering algorithm and fast forward quantum
optimization algorithm, focusing on how these techniques can be integrated into
different phases of the biomedical image analysis. In particular, this book
describes novel methods resulting from the fuzzy sets, neutrosophic sets,
clustering algorithm and fast forward quantum optimization algorithm. It also
demonstrates how a new quantum-clustering based model can be successfully
applied in the context of clustering the COVID-19 CT scans. Thanks to its
easy-to-read style and the clear explanations of the models, the book can be
used as a concise yet comprehensive reference guide to biomedical image
analysis, and will be valuable not only for graduate students, but also forresearchers and professionals working for academic, business and government

institutes and medical colleges.

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