Biomedical Image Analysis (eBook)

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.

PRITPAL SINGH, assistant professor in Central

University of Rajasthan, India.He has an academic experience of more than 7

years.

He served as

a Senior Postdoctoral Fellow in the Department of Electrical Engineering at the

Taipei National University of Technology, Taiwan, from 2019-2020. He is working as an

Adjunct Professor (Research) from November, 2020 in

the Institute of Theoretical Physics, Jagiellonian University,

Poland. He is an active research

member of Bio-Data Research Group (under TEAM-NET Program) in the Institute of Theoretical

Physics, Jagiellonian UniversityHis

His research interests include ambiguous set theory,

soft computing, optimization algorithms (especially quantum-based

optimization), time series forecasting, image analysis, fMRI data analysis,

machine learning, mathematical modeling and simulation. He has published

numerous papers in refereed SCI journals, conference proceedings, book chapters

and book.

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This book provides an in-depth study of biomedical image analysis. Itreviews and summarizes previous research work in biomedical image analysis andalso provides a brief introduction to other computation techniques, such asfuzzy sets, neutrosophic sets, clustering algorithm and fast forward quantumoptimization algorithm, focusing on how these techniques can be integrated intodifferent phases of the biomedical image analysis. In particular, this bookdescribes novel methods resulting from the fuzzy sets, neutrosophic sets,clustering algorithm and fast forward quantum optimization algorithm. It alsodemonstrates how a new quantum-clustering based model can be successfullyapplied in the context of clustering the COVID-19 CT scans. Thanks to itseasy-to-read style and the clear explanations of the models, the book can beused as a concise yet comprehensive reference guide to biomedical imageanalysis, and will be valuable not only for graduate students, but also forresearchers and professionals working for academic, business and governmentinstitutes and medical colleges.