Graphs in Biomedical Image Analysis and Integrating Medical Imaging and Non-Imaging Modalities : Second International Workshop, GRAIL 2018 and First International Workshop, Beyond MIC 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 2

This book constitutes the refereed joint proceedings of the Second International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2018 and the First International Workshop on Integrating Medical Imaging and Non-Imaging Modalities, Beyond MIC 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 6 full papers presented at GRAIL 2018 and the 5 full papers presented at BeYond MIC 2018 were carefully reviewed and selected. The GRAIL papers cover a wide range of develop graph-based models for the analysis of biomedical images and encourage the exploration of graph-based models for difficult clinical problems within a variety of biomedical imaging contexts. The Beyond MIC papers cover topics of novel methods with significant imaging and non-imaging components, addressing practical applications and new datasets Front Matter ....Pages I-XVI Front Matter ....Pages 1-1 Graph Saliency Maps Through Spectral Convolutional Networks: Application to Sex Classification with Brain Connectivity (Salim Arslan, Sofia Ira Ktena, Ben Glocker, Daniel Rueckert)....Pages 3-13 A Graph Representation and Similarity Measure for Brain Networks with Nodal Features (Yusuf Osmanlıoğlu, Birkan Tunç, Jacob A. Alappatt, Drew Parker, Junghoon Kim, Ali Shokoufandeh et al.)....Pages 14-23 Multi-modal Disease Classification in Incomplete Datasets Using Geometric Matrix Completion (Gerome Vivar, Andreas Zwergal, Nassir Navab, Seyed-Ahmad Ahmadi)....Pages 24-31 BrainParcel: A Brain Parcellation Algorithm for Cognitive State Classification (Hazal Mogultay, Fatos Tunay Yarman Vural)....Pages 32-42 Modeling Brain Networks with Artificial Neural Networks (Baran Baris Kivilcim, Itir Onal Ertugrul, Fatos T. Yarman Vural)....Pages 43-53 Front Matter ....Pages 55-55 A Bayesian Disease Progression Model for Clinical Trajectories (Yingying Zhu, Mert R. Sabuncu)....Pages 57-65 Multi-modal Brain Connectivity Study Using Deep Collaborative Learning (Wenxing Hu, Biao Cai, Vince Calhoun, Yu-Ping Wang)....Pages 66-73 Towards Subject and Diagnostic Identifiability in the Alzheimer’s Disease Spectrum Based on Functional Connectomes (Diana O. Svaldi, Joaquín Goñi, Apoorva Bharthur Sanjay, Enrico Amico, Shannon L. Risacher, John D. West et al.)....Pages 74-82 Predicting Conversion of Mild Cognitive Impairments to Alzheimer’s Disease and Exploring Impact of Neuroimaging (Yaroslav Shmulev, Mikhail Belyaev, the Alzheimer’s Disease Neuroimaging Initiative)....Pages 83-91 Cross-diagnostic Prediction of Dimensional Psychiatric Phenotypes in Anorexia Nervosa and Body Dysmorphic Disorder Using Multimodal Neuroimaging and Psychometric Data (Jamie D. Feusner, Wesley T. Kerr, Teena D. Moody, Aifeng F. Zhang, Mark S. Cohen, Alex D. Leow et al.)....Pages 92-99 Back Matter ....Pages 101-101