Hybrid Image Processing Methods for Medical Image Examination Intelligent Signal Processing and Data Analysis Series

In view of better results expected from examination of medical datasets (images) with hybrid (integration of thresholding and segmentation) image processing methods, this work focuses on implementation of possible hybrid image examination techniques for medical images. It describes various image thresholding and segmentation methods which are essential for the development of such a hybrid processing tool. Further, this book presents the essential details, such as test image preparation, implementation of a chosen thresholding operation, evaluation of threshold image, and implementation of segmentation procedure and its evaluation, supported by pertinent case studies. Aimed at researchers/graduate students in the medical image processing domain, image processing, and computer engineering, this book:

• Provides broad background on various image thresholding and segmentation techniques
• Discusses information on various assessment metrics and the confusion matrix
• Proposes integration of the thresholding technique with the bio-inspired algorithms
• Explores case studies including MRI, CT, dermoscopy, and ultrasound images
• Includes separate chapters on machine learning and deep learning for medical image processing

Venkatesan Rajinikanth is a Professor in Department of Electronics and Instrumentation Engineering at St. Joseph’s College of Engineering, Chennai 600119, Tamilnadu, India. Recently he edited a book titled ‘Advances in Artificial Intelligence Systems’, Nova Science publisher, USA. He has published more than 75 papers. He is the Associate Editor of Int. J. of Rough Sets and Data Analysis (IGI Global, US, DBLP, ACM dl) and Editing/Edited Special Issues in journals, such as Current Signal Transduction Therapy (Bentham Science), Current Medical Imaging Reviews (Bentham Science) and International Journal of Swarm Intelligence Research (IGI Global). He recently published an Indian patent titled ‘Disease Diagnosis System based on Electromyography’. His main research interests include Medical Imaging, Machine learning, and Computer Aided Diagnosis.
Research Gate: https://www.researchgate.net/profile/Venkatesan_Rajinikanth
E. Priya completed her Ph.D at MIT Campus, Anna University in the field of “Automated analysis using image processing and artificial intelligence for the diagnosis of tuberculosis images”. At present she is a Professor at the Department of Electronics and Communication Engineering, Sri Sairam Engineering College, Affiliated to Anna University, Chennai. She has 17 years of teaching experience, 4 years of research experience and 3 years of industrial experience. She is a recipient of DST-PURSE fellow and a project participant of India-South African collaborative project titled “Development of computing tools for decision support in health assessment in rural areas”. Her areas of interest include bio-medical imaging, image processing, signal processing, application of artificial intelligence and machine learning techniques. She has published papers in refereed International Journals, Conferences and book chapters in the area of medical imaging and infectious diseases.
Research Gate: https://www.researchgate.net/profile/Ebenezer_Priya
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