Yang co-authors book on deep learning and convolutional neural network for biomedical image computing

This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, microscopic image analysis, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. This book describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database. Dr. Yang is the founder of the Biomedical Image Computing and Imaging Informatics (BICI2) lab (http://www.bme.ufl.edu/labs/yang/). His major research interests are focus on biomedical image analysis and imaging informatics, computer vision, biomedical informatics and machine learning.