Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries 4th International Workshop, BrainLes 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Revised Selected Papers, Part I. Image Processing, Computer V

This two-volume set LNCS 11383 and 11384 constitutes revised selected papers from the 4th International MICCAI Brainlesion Workshop, BrainLes 2018, as well as the International Multimodal Brain Tumor Segmentation, BraTS, Ischemic Stroke Lesion Segmentation, ISLES, MR Brain Image Segmentation, MRBrainS18, Computational Precision Medicine, CPM, and Stroke Workshop on Imaging and Treatment Challenges, SWITCH, which were held jointly at the Medical Image Computing for Computer Assisted Intervention Conference, MICCAI, in Granada, Spain, in September 2018. The 92 papers presented in this volume were carefully reviewed and selected from 95 submissions. They were organized in topical sections named: brain lesion image analysis; brain tumor image segmentation; ischemic stroke lesion image segmentation; grand challenge on MR brain segmentation; computational precision medicine; stroke workshop on imaging and treatment challenges. Front Matter ....Pages I-XXI Front Matter ....Pages 1-1 Multimodal Patho-Connectomics of Brain Injury (Ragini Verma, Yusuf Osmanlioglu, Abdol Aziz Ould Ismail)....Pages 3-14 CT Brain Perfusion: A Clinical Perspective (Arsany Hakim, Roland Wiest)....Pages 15-24 Adverse Effects of Image Tiling on Convolutional Neural Networks (G. Anthony Reina, Ravi Panchumarthy)....Pages 25-36 An Update on Machine Learning in Neuro-Oncology Diagnostics (Thomas C. Booth)....Pages 37-44 Front Matter ....Pages 45-45 MIMoSA: An Approach to Automatically Segment T2 Hyperintense and T1 Hypointense Lesions in Multiple Sclerosis (Alessandra M. Valcarcel, Kristin A. Linn, Fariha Khalid, Simon N. Vandekar, Shahamat Tauhid, Theodore D. Satterthwaite et al.)....Pages 47-56 CNN Prediction of Future Disease Activity for Multiple Sclerosis Patients from Baseline MRI and Lesion Labels (Nazanin Mohammadi Sepahvand, Tal Hassner, Douglas L. Arnold, Tal Arbel)....Pages 57-69 Learning Data Augmentation for Brain Tumor Segmentation with Coarse-to-Fine Generative Adversarial Networks (Tony C. W. Mok, Albert C. S. Chung)....Pages 70-80 Multipath Densely Connected Convolutional Neural Network for Brain Tumor Segmentation (Cong Liu, Weixin Si, Yinling Qian, Xiangyun Liao, Qiong Wang, Yong Guo et al.)....Pages 81-91 Multi-institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation (Micah J. Sheller, G. Anthony Reina, Brandon Edwards, Jason Martin, Spyridon Bakas)....Pages 92-104 Patient-Specific Registration of Pre-operative and Post-recurrence Brain Tumor MRI Scans (Xu Han, Spyridon Bakas, Roland Kwitt, Stephen Aylward, Hamed Akbari, Michel Bilello et al.)....Pages 105-114 Segmentation of Post-operative Glioblastoma in MRI by U-Net with Patient-Specific Interactive Refinement (Ashis Kumar Dhara, Kalyan Ram Ayyalasomayajula, Erik Arvids, Markus Fahlström, Johan Wikström, Elna-Marie Larsson et al.)....Pages 115-122 Characterizing Peritumoral Tissue Using DTI-Based Free Water Elimination (Abdol Aziz Ould Ismail, Drew Parker, Moises Hernandez-Fernandez, Steven Brem, Simon Alexander, Ofer Pasternak et al.)....Pages 123-131 Deep 2D Encoder-Decoder Convolutional Neural Network for Multiple Sclerosis Lesion Segmentation in Brain MRI (Shahab Aslani, Michael Dayan, Vittorio Murino, Diego Sona)....Pages 132-141 Shallow vs Deep Learning Architectures for White Matter Lesion Segmentation in the Early Stages of Multiple Sclerosis (Francesco La Rosa, Mário João Fartaria, Tobias Kober, Jonas Richiardi, Cristina Granziera, Jean-Philippe Thiran et al.)....Pages 142-151 Detection of Midline Brain Abnormalities Using Convolutional Neural Networks (Aleix Solanes, Joaquim Radua, Laura Igual)....Pages 152-160 Deep Autoencoding Models for Unsupervised Anomaly Segmentation in Brain MR Images (Christoph Baur, Benedikt Wiestler, Shadi Albarqouni, Nassir Navab)....Pages 161-169 Brain Tumor Detection and Classification from Multi-sequence MRI: Study Using ConvNets (Subhashis Banerjee, Sushmita Mitra, Francesco Masulli, Stefano Rovetta)....Pages 170-179 Voxel-Wise Comparison with a-contrario Analysis for Automated Segmentation of Multiple Sclerosis Lesions from Multimodal MRI (Francesca Galassi, Olivier Commowick, Emmanuel Vallee, Christian Barillot)....Pages 180-188 A Graph Based Similarity Measure for Assessing Altered Connectivity in Traumatic Brain Injury (Yusuf Osmanlıoğlu, Jacob A. Alappatt, Drew Parker, Junghoon Kim, Ragini Verma)....Pages 189-198 Multi-scale Convolutional-Stack Aggregation for Robust White Matter Hyperintensities Segmentation (Hongwei Li, Jianguo Zhang, Mark Muehlau, Jan Kirschke, Bjoern Menze)....Pages 199-207 Holistic Brain Tumor Screening and Classification Based on DenseNet and Recurrent Neural Network (Yufan Zhou, Zheshuo Li, Hong Zhu, Changyou Chen, Mingchen Gao, Kai Xu et al.)....Pages 208-217 3D Texture Feature Learning for Noninvasive Estimation of Gliomas Pathological Subtype (Guoqing Wu, Yuanyuan Wang, Jinhua Yu)....Pages 218-227 Pathology Segmentation Using Distributional Differences to Images of Healthy Origin (Simon Andermatt, Antal Horváth, Simon Pezold, Philippe Cattin)....Pages 228-238 Multi-stage Association Analysis of Glioblastoma Gene Expressions with Texture and Spatial Patterns (Samar S. M. Elsheikh, Spyridon Bakas, Nicola J. Mulder, Emile R. Chimusa, Christos Davatzikos, Alessandro Crimi)....Pages 239-250 Front Matter ....Pages 251-251 Stroke Lesion Segmentation with 2D Novel CNN Pipeline and Novel Loss Function (Pengbo Liu)....Pages 253-262 Contra-Lateral Information CNN for Core Lesion Segmentation Based on Native CTP in Acute Stroke (Jeroen Bertels, David Robben, Dirk Vandermeulen, Paul Suetens)....Pages 263-270 Dense Multi-path U-Net for Ischemic Stroke Lesion Segmentation in Multiple Image Modalities (Jose Dolz, Ismail Ben Ayed, Christian Desrosiers)....Pages 271-282 Multi-scale Deep Convolutional Neural Network for Stroke Lesions Segmentation on CT Images (Liangliang Liu, Shuai Yang, Li Meng, Min Li, Jianxin Wang)....Pages 283-291 Ischemic Stroke Lesion Segmentation Using Adversarial Learning (Mobarakol Islam, N. Rajiv Vaidyanathan, V. Jeya Maria Jose, Hongliang Ren)....Pages 292-300 V-Net and U-Net for Ischemic Stroke Lesion Segmentation in a Small Dataset of Perfusion Data (Gustavo Retuci Pinheiro, Raphael Voltoline, Mariana Bento, Leticia Rittner)....Pages 301-309 Integrated Extractor, Generator and Segmentor for Ischemic Stroke Lesion Segmentation (Tao Song, Ning Huang)....Pages 310-318 ISLES Challenge: U-Shaped Convolution Neural Network with Dilated Convolution for 3D Stroke Lesion Segmentation (Alzbeta Tureckova, Antonio J. Rodríguez-Sánchez)....Pages 319-327 Fully Automatic Segmentation for Ischemic Stroke Using CT Perfusion Maps (Vikas Kumar Anand, Mahendra Khened, Varghese Alex, Ganapathy Krishnamurthi)....Pages 328-334 Combining Good Old Random Forest and DeepLabv3+ for ISLES 2018 CT-Based Stroke Segmentation (Lasse Böhme, Frederic Madesta, Thilo Sentker, René Werner)....Pages 335-342 Volumetric Adversarial Training for Ischemic Stroke Lesion Segmentation (Hao-Yu Yang)....Pages 343-351 Ischemic Stroke Lesion Segmentation in CT Perfusion Scans Using Pyramid Pooling and Focal Loss (S. Mazdak Abulnaga, Jonathan Rubin)....Pages 352-363 Front Matter ....Pages 365-365 MixNet: Multi-modality Mix Network for Brain Segmentation (Long Chen, Dorit Merhof)....Pages 367-377 A Skip-Connected 3D DenseNet Networks with Adversarial Training for Volumetric Segmentation (Toan Duc Bui, Sang-il Ahn, Yongwoo Lee, Jitae Shin)....Pages 378-384 Automatic Brain Structures Segmentation Using Deep Residual Dilated U-Net (Hongwei Li, Andrii Zhygallo, Bjoern Menze)....Pages 385-393 3D Patchwise U-Net with Transition Layers for MR Brain Segmentation (Miguel Luna, Sang Hyun Park)....Pages 394-403 Front Matter ....Pages 405-405 Dropout-Enabled Ensemble Learning for Multi-scale Biomedical Data (Alexandre Momeni, Marc Thibault, Olivier Gevaert)....Pages 407-415 A Combined Radio-Histological Approach for Classification of Low Grade Gliomas (Aditya Bagari, Ashish Kumar, Avinash Kori, Mahendra Khened, Ganapathy Krishnamurthi)....Pages 416-427 Robust Segmentation of Nucleus in Histopathology Images via Mask R-CNN (Xinpeng Xie, Yuexiang Li, Menglu Zhang, Linlin Shen)....Pages 428-436 Front Matter ....Pages 437-437 Perfusion Parameter Estimation Using Neural Networks and Data Augmentation (David Robben, Paul Suetens)....Pages 439-446 Synthetic Perfusion Maps: Imaging Perfusion Deficits in DSC-MRI with Deep Learning (Andreas Hess, Raphael Meier, Johannes Kaesmacher, Simon Jung, Fabien Scalzo, David Liebeskind et al.)....Pages 447-455 ICHNet: Intracerebral Hemorrhage (ICH) Segmentation Using Deep Learning (Mobarakol Islam, Parita Sanghani, Angela An Qi See, Michael Lucas James, Nicolas Kon Kam King, Hongliang Ren)....Pages 456-463 Can Diffusion MRI Reveal Stroke-Induced Microstructural Changes in GM? (Lorenza Brusini, Ilaria Boscolo Galazzo, Mauro Zucchelli, Cristina Granziera, Gloria Menegaz)....Pages 464-471 Back Matter ....Pages 473-477