Deep Learning in Medical Image Analysis

Gobert Lee is a lecturer in Statistical Science and the Director of Studies in Mathematics and Statistics at the College of Science and Engineering, and a research member of the Medical Device Research Institute, Flinders University, Adelaide, Australia. Gobert's research interests include statistical pattern recognition, medical image segmentation, computer-aided-diagnosis systems, breast cancer detection and analysis, multi-organ CT segmentation and human voxel model generation.

Hiroshi Fujita is a Research Professor/Emeritus Professor of Gifu University. He is a member of the Society for Medical Image Information (president), the Research Group on Medical Imaging (adviser), the Japan Society for Medical Image Engineering (director), and some other societies. His research interests include computer-aided diagnosis system, image analysis and processing, and image evaluation in medicine. He has published over 1000 papers in Journals, Proceedings, Book chapters and Scientific Magazines.

Deep Learning in Medical Image Analysis.- Medical Image Synthesis via Deep Learning.- Deep Learning for Pulmonary Image Analysis: Classification, Detection, and Segmentation.- Deep Learning Computer Aided Diagnosis for Breast Lesion in Digital Mammogram.- Decision support system for lung cancer using PET/CT and microscopic images.- Lesion Image Synthesis using DCGANs for Metastatic Liver Cancer Detection.- Retinopathy analysis based on deep convolution neural network.- Diagnosis of Glaucoma on retinal fundus images using deep learning: detection of nerve fiber layer defect and optic disc analysis.- Automatic segmentation of multiple organs on 3D CT images by using deep learning approaches.- Techniques and Applications in Skin OCT Analysis.- Deep Learning Technique for Musculoskeletal Analysis.- Index.