(Ebook) OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging: Second International Workshop, OR 2.0 2019, and Second International Workshop, MLCN 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019 by Luping Zhou, Duygu Sarikaya, Seyed Mostafa Kia, Stefanie Speidel, Anand Malpani, Daniel Hashimoto, Mohamad Habes, Tommy Löfstedt, Kerstin Ritter, Hongzhi Wang ISBN 9783030326944, 9783030326951, 3030326942, 3030326950

(Ebook) OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging: Second International Workshop, OR 2.0 2019, and Second International Workshop, MLCN 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019 by Luping Zhou, Duygu Sarikaya, Seyed Mostafa Kia, Stefanie Speidel, Anand Malpani, Daniel Hashimoto, Mohamad Habes, Tommy Löfstedt, Kerstin Ritter, Hongzhi Wang ISBN 9783030326944, 9783030326951, 3030326942, 3030326950

This book constitutes the refereed proceedings of the Second International Workshop on Context-Aware Surgical Theaters, OR 2.0 2019, and the Second International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019.For OR 2.0 all 6 submissions were accepted for publication. They aim to highlight the potential use of machine vision and perception, robotics, surgical simulation and modeling, multi-modal data fusion and visualization, image analysis, advanced imaging, advanced display technologies, human-computer interfaces, sensors, wearable and implantable electronics and robots, visual attention models, cognitive models, decision support networks to enhance surgical procedural assistance, context-awareness and team communication in the operating theater, human-robot collaborative systems, and surgical training and assessment.MLCN 2019 accepted 6 papers out of 7 submissions for publication. They focus on addressing the problems of applying machine learning to large and multi-site clinical neuroimaging datasets. The workshop aimed to bring together experts in both machine learning and clinical neuroimaging to discuss and hopefully bridge the existing challenges of applied machine learning in clinical neuroscience.