Recent Trends in Computer-aided Diagnostic Systems for Skin Diseases

Theory, Implementation, and Analysis

Häftad, Engelska, 2021

1 256 kr

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Beskrivning

Recent Trends in Computer-aided Diagnostic Systems for Skin Diseases: Theory, Implementation, and Analysis provides comprehensive coverage on the development of computer-aided diagnostic (CAD) systems employing image processing and machine learning tools for improved, uniform evaluation and diagnosis (avoiding subjective judgment) of skin disorders.

The methods and tools are described in a general way so that these tools can be applied not only for skin diseases but also for a wide range of analogous problems in the domain of biomedical systems. Moreover, quantification of clinically relevant information that can associate the findings of physicians/experts is the most challenging task of any CAD system.

This book gives all the details in a step-by-step form for different modules so that the readers can develop each of the modules like preprocessing, feature extraction/learning, disease classification, as well as an entire expert diagnosis system themselves for their own applications.

Demonstrates extensive calculations for illustrating the theoretical analysis of advanced image processing and machine learning techniques
Provides a comprehensive coverage on the development of various signal processing tools for the extraction of statistical and clinically correlated features from skin lesion images
Describes image processing and machine learning techniques for improved uniform evaluation and diagnosis of skin disorders

Produktinformation

Utgivningsdatum:2021-11-05
Mått:191 x 235 x undefined mm
Vikt:430 g
Format:Häftad
Språk:Engelska
Antal sidor:204
Förlag:Elsevier Science
ISBN:9780323912112

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Mer om författaren

Dr. Saptarshi Chatterjee has completed his PhD from the Electrical Engineering Department, Jadavpur University, Kolkata, India. He has significant technical research publications in archived journals and peer-reviewed conferences. He is also the recipient of Visvesvaraya PhD Fellowship, MeitY, Government of India, and two Best Paper Awards in international conferences. He is a member of IEEE Signal Processing Society. His research initiatives are focused in the area of signal processing, image processing, and condition monitoring of biomedical systems. Dr. Debangshu Dey is working as an assistant professor in the Electrical Engineering Department, Jadavpur University, Kolkata, India. Dr. Dey has published more than 50 research papers in various international journals in the fields of his research and coauthored one book from Springer-Verlag London. Four patents have been granted to him including a US Patent. He is also the recipient of IEI Young Engineer Award in 2014 and two Best Paper Awards in International Conferences. His areas of interest are applications of signal and image conditioning and processing tools in electrical and biomedical systems, condition monitoring of electrical equipment, noninvasive testing, intelligent instrumentation, and measurements related to condition assessment techniques. Prof. Sugata Munshi has worked as an engineer in the Plasma Physics Division of Saha Institute of Nuclear Physics, India, from 1985 to 1990. In 1986, he underwent training on “Tokamak machine in the “Heavy Engineering Works of Toshiba Corporation in Japan. In 1990, he joined the Electrical Engineering Department of Jadavpur University as a faculty member. He has published about 45 research papers in refereed journals. He was the joint recipient of The President of India’s Prize (English) in 1989–90, The Pandit Madan Mohan Malaviya Memorial Prize in 1989–90, The Sir Thomas Ward Memorial Prize in 1994–95, The Tata Rao Medal in 1996–97, all awarded by the Institution of Engineers (India), and also Certificates of Merit from IE (India) in 1996–97. At present, he is a professor in this department. His current fields of interest are signal processing, sensor systems, and intelligent instrumentation.

Innehållsförteckning

1. Introduction2. Preprocessing and segmentation of skin lesion images3. Extraction of effective hand crafted features from dermoscopic images4. Feature selection and classification5. Development of expert system for skin disease identification6. Conclusions and future scope of work