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Deep Neural Networks for Multimodal Imaging and Biomedical ApplicationsНазвание: Deep Neural Networks for Multimodal Imaging and Biomedical Applications
Автор: Annamalai Suresh, R. Udendhran, S. Vimal
Издательство: IGI Global
Год: 2020
Страниц: 310
Язык: английский
Формат: pdf (true)
Размер: 11.8 MB

The field of healthcare is seeing a rapid expansion of technological advancement within current medical practices. The implementation of technologies including neural networks, multi-model imaging, genetic algorithms, and soft computing are assisting in predicting and identifying diseases, diagnosing cancer, and the examination of cells. Implementing these biomedical technologies remains a challenge for hospitals worldwide, creating a need for research on the specific applications of these computational techniques.

Deep Neural Networks for Multimodal Imaging and Biomedical Applications provides research exploring the theoretical and practical aspects of emerging data computing methods and imaging techniques within healthcare and biomedicine. The publication provides a complete set of information in a single module starting from developing deep neural networks to predicting disease by employing multi-modal imaging. Featuring coverage on a broad range of topics such as prediction models, edge computing, and quantitative measurements, this book is ideally designed for researchers, academicians, physicians, IT consultants, medical software developers, practitioners, policymakers, scholars, and students seeking current research on biomedical advancements and developing computational methods in healthcare.

Deep Learning is quickly growing and has shown enhanced performance in medical applications. It has also been widely extended in academia and industry. The utilization of various deep learning methods on medical imaging endeavours to create systems that can help in the identifcation of disease and the automation of interpreting biomedical images to help treatment planning. New advancements in Machine Learning (ML) are primarily about Deep Learning employed for identifying, classifying, and quantifying patterns in images in the medical feld. Deep Learning, a more precise convolutional neural network has given excellent performance over Machine Learning in solving visual problems.

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