Springer Retinal Optical Coherence Tomography Image Analysis (Biological and Medical Physics, Biomedical Engineering)

Product Description This book introduces the latest optical coherence tomography (OCT) imaging and computerized automatic image analysis techniques, and their applications in the diagnosis and treatment of retinal diseases. Discussing the basic principles and the clinical applications of OCT imaging, OCT image preprocessing, as well as the automatic detection and quantitative analysis of retinal anatomy and pathology, it includes a wealth of clinical OCT images, and state-of-the-art research that applies novel image processing, pattern recognition and machine learning methods to real clinical data. It is a valuable resource for researchers in both medical image processing and ophthalmic imaging. From the Back Cover This book introduces the latest optical coherence tomography (OCT) imaging and computerized automatic image analysis techniques, and their applications in the diagnosis and treatment of retinal diseases. Discussing the basic principles and the clinical applications of OCT imaging, OCT image preprocessing, as well as the automatic detection and quantitative analysis of retinal anatomy and pathology, it includes a wealth of clinical OCT images, and state-of-the-art research that applies novel image processing, pattern recognition and machine learning methods to real clinical data. It is a valuable resource for researchers in both medical image processing and ophthalmic imaging. About the Author Xinjian Chen, IEEE Senior Member, received his Ph.D. degree from the Institute of Automation, Chinese Academy of Sciences in 2006. After graduation, he worked on research projects with several prestigious groups: Microsoft Research Asia, Beijing, China (2006-2007); Medical Image Processing Group, University of Pennsylvania (2008-2009); Department of Radiology and Image Sciences, National Institutes of Health  (2009-2011); and Department of Electrical and Computer Engineering, University of Iowa  (2011-2012). In 2012, he joined the School of Electrical and Information Engineering, Soochow University where he serves as a Distinguished Professor and Director of Medical Image Processing, Analysis and Visualization Laboratory. Under his leadership, the laboratory has evolved with a strong group of 8 faculty members and 30 postgraduate students working towards PhD and MS programs. The laboratory has received more than 10 National and Provincial grants, including the prestigious Young Scientist grant with Xinjian as the PI from National Basic Research Program of China (973). Dr. Chen is a recipient of the National Science Fund for Outstanding Young Scholars, China (2016), National One Thousand Young Talents Award, China (2012), Jiangsu Provincial High Level Creative Talents Award (2013), Jiangsu Provincial Peak Talents of Six Categories Award (2012), Beijing Science and Technology Advancement Award (2011), Chinese Academy of Sciences President Excellence Award (2006), Important Technology Innovation Award of China (2005), and National Technology Advancement Award of China (2004). His research interests include medical image processing and analysis, pattern recognition, machine learning, and their applications. Dr. Chen has published more than 100 peer-reviewed papers in prestigious international journals and conferences including IEEE Transactions on Medical Imaging, IEEE Transactions on Biomedical Engineering, Medical Physics, IEEE Transactions Information Technology in Biomedicine, and Radiology, etc. He has served as Workshop Chair for MICCAI OMIA2014, Co-Chair for MICCAI OMIA2015, 2016, and 2017. He has also served as the Workshop Chair for International Medical Imaging Workshop at Suzhou 2013, 2014, 2015 and 2017. He has served as Associate Editor for IEEE Transactions on Medical Imaging, and IEEE Journal of Translational Engineering in Health and Medicine. He also holds 10 granted patents and 20 pending status patents. Fei Shi received her bachelor’s degree in Information and Electronics Engin