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
Despite the popularity of sport in contemporary China, the practice of physical education is not indigenous to its culture. Strenuous physical activity was traditionally linked to low class and status in the pre-modern Chinese society. The concept of modern PE was introduced to China by Western Christian missionaries and directors of the Young Men’s Christian Association (YMCA). It then grew from a tool for Christian evangelism to a strategic instrument in Chinese nation-building. This book examines the transformation of Chinese attitudes toward PE and sport, drawing on the concepts of cultural imperialism and nationalism to understand how an imported Western activity became a key aspect of modernization for the Chinese state. More specifically, it looks at the relationship between Christianity and the rise of Chinese nationalism between 1840 and 1937. Combining historical insight with original research, this book sheds new light on the evolution of PE and sport in modern China. It is fascinating reading for all those with an interest in sports history, Chinese culture and society, Christianity, physical education or the sociology of sport.
With the ever-increasing usage of distance learning programs in academia, the need for well-designed automated systems has become vital to the success of open and distance education. Practical solutions should be discovered and disseminated to meet the software needs of instructors, academic researchers, and software engineers. System and Technology Advancements in Distance Learning meets this need, outlining computational methods, algorithms, implemented prototype systems, and applications of open and distance learning. It is targeted toward academic researchers and engineers who work with distance learning programs and software systems, as well as general participants of distance education.
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
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