Deep Learning in Medical Image Analysis

<P>This book is designed as a reference text and provides a comprehensive overview of conceptual and practical knowledge about deep learning in medical image processing techniques. The post-pandemic situation teaches us the importance of doctors, medical analysis, and diagnosis of diseases in a rapid manner. This book provides a snapshot of the state of current research between deep learning, medical image processing, and health care with special emphasis on saving human life. The chapters cover a range of advanced technologies related to patient health monitoring, predicting diseases from genomic data, detecting artefactual events in vital signs monitoring data, and managing chronic diseases. This book</P><UL><LI>Delivers an ideal introduction to image processing in medicine, emphasizing the clinical relevance and special requirements of the field</LI><LI>Presents key principles by implementing algorithms from scratch and using simple MATLAB®/Octave scripts with image data</LI><LI>Provides an overview of the physics of medical image processing alongside discussing image formats and data storage, intensity transforms, filtering of images and applications of the Fourier transform, three-dimensional spatial transforms, volume rendering, image registration, and tomographic reconstruction</LI><LI>Highlights the new potential applications of machine learning techniques to the solution of important problems in biomedical image applications</LI></UL><P>This book is for students, scholars, and professionals of biomedical technology and healthcare data analytics.</P>