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Biomedical Image Analysis [electronic resource] : Special Applications in MRIs and CT scans / by Pritpal Singh.

By: Singh, Pritpal [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Brain Informatics and Health: Publisher: Singapore : Springer Nature Singapore : Imprint: Springer, 2024Edition: 1st ed. 2024.Description: XI, 166 p. 1 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9789819999392.Subject(s): Image processing | Artificial intelligence | Machine learning | Artificial intelligence -- Data processing | Image Processing | Artificial Intelligence | Machine Learning | Data ScienceAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 621.382 Online resources: Click here to access online
Contents:
Chapter 1 Parkinson's disease MRIs analysis using fuzzy clustering approach -- Chapter 2 Parkinson's disease MRIs analysis using neutrosophic segmentation approach -- Chapter 3 Parkinson's disease MRIs analysis using neutrosophic clustering approach -- Chapter 4 Brain tumor segmentation using type-2 neutrosophic thresholding approach -- Chapter 5 COVID-19 scan image segmentation using quantum-clustering approach -- Chapter 6 Empirical Analyses.
In: Springer Nature eBookSummary: 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 for researchers and professionals working for academic, business and government institutes and medical colleges.
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Chapter 1 Parkinson's disease MRIs analysis using fuzzy clustering approach -- Chapter 2 Parkinson's disease MRIs analysis using neutrosophic segmentation approach -- Chapter 3 Parkinson's disease MRIs analysis using neutrosophic clustering approach -- Chapter 4 Brain tumor segmentation using type-2 neutrosophic thresholding approach -- Chapter 5 COVID-19 scan image segmentation using quantum-clustering approach -- Chapter 6 Empirical Analyses.

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 for researchers and professionals working for academic, business and government institutes and medical colleges.

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