MEDICAL COMPUTER VISION

Modern learning algorithms make the promise of bridging the semantic gap between images and diagnoses and even reaching superhuman performance. The goal of this workshop is to explore the use of "big data" algorithms for harvesting, organizing and learning from large-scale medical imaging data sets and for general-purpose automatic understanding of medical images. This includes modern, scalable and efficient algorithms for automatic localization, segmentation, registration and characterization of anatomical features and anomalies. We encourage the submission of original papers that propose new methodology strongly motivated by a clinical application. Submissions will be at the interface of big data algorithms, computer vision, machine learning and medical image analysis... The event is in continuation of previous MCV workshops at MICCAI 2010, CVPR 2012, MICCAI 2012, MICCAI 2013, MICCAI 2014, CVPR 2015, and MICCAI 2015... Methods dealing with incomplete-, weak- or noisy annotation of..