MICCAI 2016 Daily - Thursday

The paper they are presenting at MICCAI on Thursday (see their poster PS5-21 from 10:30-12:00) is about a co-registration and segmentation framework that combines ideas from these fields towards producing automatic annotations of sub-cortical structures in brain MR images. These annotations are of great importance for diagnosis and characterization of different neurodegenerative and neuropsychiatric disorders, including schizophrenia, Alzheimer's disease, attention deficit, and sub-types of epilepsy. What I found most interesting about their method in comparison with previous multi-atlas segmentation approaches, is that instead of using expert manual annotations (which are difficult to obtain and highly time- consuming), they showed that it is possible to use semantic priors learned with any machine learning technique to guide both, groupwise registration and segmentation processes. For that, they contacted Stavros Tsogkas, a deep learning and computer vision researcher currently working at University of Toronto, to design a convolutional neural network architecture that was finally used to produce the semantic priors. Their work was not only a nice example of science collaboration, but it also produced really promising results which may lead to future better understanding of structural alterations related to different brain disorders. 19 MICCAI Daily: Thursday “ Mahsa had experience on brain image segmentation techniques, and during the last year she was particularly interested in multi-atlas segmentation ” Presentation