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ORCID4th Brainles@MICCAI 2018: Granada, Spain
- Alessandro Crimi, Spyridon Bakas, Hugo J. Kuijf, Farahani Keyvan, Mauricio Reyes, Theo van Walsum:
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. Lecture Notes in Computer Science 11383, Springer 2019, ISBN 978-3-030-11722-1
Invited Talk
- Ragini Verma, Yusuf Osmanlioglu
, Abdol Aziz Ould Ismail:
Multimodal Patho-Connectomics of Brain Injury. 3-14 - Arsany Hakim, Roland Wiest:
CT Brain Perfusion: A Clinical Perspective. 15-24 - G. Anthony Reina, Ravi Panchumarthy:
Adverse Effects of Image Tiling on Convolutional Neural Networks. 25-36 - Thomas C. Booth:
An Update on Machine Learning in Neuro-Oncology Diagnostics. 37-44
Brain Lesion Image Analysis
- Alessandra M. Valcarcel, Kristin A. Linn, Fariha Khalid, Simon N. Vandekar, Shahamat Tauhid, Theodore D. Satterthwaite, John Muschelli, Rohit Bakshi, Russell T. Shinohara:
MIMoSA: An Approach to Automatically Segment T2 Hyperintense and T1 Hypointense Lesions in Multiple Sclerosis. 47-56 - Nazanin Mohammadi Sepahvand, Tal Hassner, Douglas L. Arnold, Tal Arbel:
CNN Prediction of Future Disease Activity for Multiple Sclerosis Patients from Baseline MRI and Lesion Labels. 57-69 - Tony C. W. Mok, Albert C. S. Chung:
Learning Data Augmentation for Brain Tumor Segmentation with Coarse-to-Fine Generative Adversarial Networks. 70-80 - Cong Liu, Weixin Si, Yinling Qian, Xiangyun Liao, Qiong Wang, Yong Guo, Pheng-Ann Heng:
Multipath Densely Connected Convolutional Neural Network for Brain Tumor Segmentation. 81-91 - Micah J. Sheller, G. Anthony Reina, Brandon Edwards, Jason Martin, Spyridon Bakas:
Multi-institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation. 92-104 - Xu Han, Spyridon Bakas, Roland Kwitt, Stephen R. Aylward, Hamed Akbari, Michel Bilello, Christos Davatzikos, Marc Niethammer:
Patient-Specific Registration of Pre-operative and Post-recurrence Brain Tumor MRI Scans. 105-114 - Ashis Kumar Dhara, Kalyan Ram Ayyalasomayajula, Erik Arvids, Markus Fahlström, Johan Wikström, Elna-Marie Larsson, Robin Strand:
Segmentation of Post-operative Glioblastoma in MRI by U-Net with Patient-Specific Interactive Refinement. 115-122 - Abdol Aziz Ould Ismail, Drew Parker, Moisés Hernández-Fernández, Steven Brem, Simon Alexander, Ofer Pasternak, Emmanuel Caruyer, Ragini Verma:
Characterizing Peritumoral Tissue Using DTI-Based Free Water Elimination. 123-131 - Shahab Aslani, Michael Dayan, Vittorio Murino, Diego Sona:
Deep 2D Encoder-Decoder Convolutional Neural Network for Multiple Sclerosis Lesion Segmentation in Brain MRI. 132-141 - Francesco La Rosa, Mário João Fartaria, Tobias Kober, Jonas Richiardi, Cristina Granziera, Jean-Philippe Thiran, Meritxell Bach Cuadra:
Shallow vs Deep Learning Architectures for White Matter Lesion Segmentation in the Early Stages of Multiple Sclerosis. 142-151 - Aleix Solanes, Joaquim Radua, Laura Igual:
Detection of Midline Brain Abnormalities Using Convolutional Neural Networks. 152-160 - Christoph Baur, Benedikt Wiestler, Shadi Albarqouni, Nassir Navab:
Deep Autoencoding Models for Unsupervised Anomaly Segmentation in Brain MR Images. 161-169 - Subhashis Banerjee, Sushmita Mitra, Francesco Masulli, Stefano Rovetta:
Brain Tumor Detection and Classification from Multi-sequence MRI: Study Using ConvNets. 170-179 - Francesca Galassi, Olivier Commowick, Emmanuel Vallée, Christian Barillot:
Voxel-Wise Comparison with a-contrario Analysis for Automated Segmentation of Multiple Sclerosis Lesions from Multimodal MRI. 180-188 - Yusuf Osmanlioglu, Jacob A. Alappatt, Drew Parker, Junghoon Kim, Ragini Verma:
A Graph Based Similarity Measure for Assessing Altered Connectivity in Traumatic Brain Injury. 189-198 - Hongwei Li, Jianguo Zhang, Mark Mühlau, Jan Kirschke, Bjoern H. Menze:
Multi-scale Convolutional-Stack Aggregation for Robust White Matter Hyperintensities Segmentation. 199-207 - Yufan Zhou, Zheshuo Li, Hong Zhu, Changyou Chen, Mingchen Gao, Kai Xu, Jinhui Xu:
Holistic Brain Tumor Screening and Classification Based on DenseNet and Recurrent Neural Network. 208-217 - Guoqing Wu, Yuanyuan Wang, Jinhua Yu:
3D Texture Feature Learning for Noninvasive Estimation of Gliomas Pathological Subtype. 218-227 - Simon Andermatt, Antal Horváth, Simon Pezold, Philippe C. Cattin:
Pathology Segmentation Using Distributional Differences to Images of Healthy Origin. 228-238 - Samar S. M. Elsheikh, Spyridon Bakas, Nicola J. Mulder, Emile R. Chimusa, Christos Davatzikos, Alessandro Crimi:
Multi-stage Association Analysis of Glioblastoma Gene Expressions with Texture and Spatial Patterns. 239-250
Ischemic Stroke Lesion Image Segmentation
- Pengbo Liu:
Stroke Lesion Segmentation with 2D Novel CNN Pipeline and Novel Loss Function. 253-262 - Jeroen Bertels, David Robben, Dirk Vandermeulen, Paul Suetens:
Contra-Lateral Information CNN for Core Lesion Segmentation Based on Native CTP in Acute Stroke. 263-270 - Jose Dolz, Ismail Ben Ayed, Christian Desrosiers:
Dense Multi-path U-Net for Ischemic Stroke Lesion Segmentation in Multiple Image Modalities. 271-282 - Liangliang Liu, Shuai Yang, Li Meng, Min Li, Jianxin Wang:
Multi-scale Deep Convolutional Neural Network for Stroke Lesions Segmentation on CT Images. 283-291 - Mobarakol Islam, N. Rajiv Vaidyanathan, V. Jeya Maria Jose, Hongliang Ren:
Ischemic Stroke Lesion Segmentation Using Adversarial Learning. 292-300 - Gustavo Retuci Pinheiro, Raphael Voltoline, Mariana P. Bento, Letícia Rittner:
V-Net and U-Net for Ischemic Stroke Lesion Segmentation in a Small Dataset of Perfusion Data. 301-309 - Tao Song, Ning Huang:
Integrated Extractor, Generator and Segmentor for Ischemic Stroke Lesion Segmentation. 310-318 - Alzbeta Tureckova, Antonio Jose Rodríguez-Sánchez:
ISLES Challenge: U-Shaped Convolution Neural Network with Dilated Convolution for 3D Stroke Lesion Segmentation. 319-327 - Vikas Kumar Anand, Mahendra Khened, Alex Varghese, Ganapathy Krishnamurthi:
Fully Automatic Segmentation for Ischemic Stroke Using CT Perfusion Maps. 328-334 - Lasse Böhme, Frederic Madesta, Thilo Sentker, René Werner:
Combining Good Old Random Forest and DeepLabv3+ for ISLES 2018 CT-Based Stroke Segmentation. 335-342 - Hao-Yu Yang:
Volumetric Adversarial Training for Ischemic Stroke Lesion Segmentation. 343-351 - Sayed Mazdak Abulnaga, Jonathan Rubin:
Ischemic Stroke Lesion Segmentation in CT Perfusion Scans Using Pyramid Pooling and Focal Loss. 352-363
Grand Challenge on MR Brain Segmentation
- Long Chen, Dorit Merhof:
MixNet: Multi-modality Mix Network for Brain Segmentation. 367-377 - Toan Duc Bui, Sang-il Ahn, Yongwoo Lee, Jitae Shin:
A Skip-Connected 3D DenseNet Networks with Adversarial Training for Volumetric Segmentation. 378-384 - Hongwei Li, Andrii Zhygallo, Bjoern H. Menze:
Automatic Brain Structures Segmentation Using Deep Residual Dilated U-Net. 385-393 - Miguel Luna, Sang Hyun Park:
3D Patchwise U-Net with Transition Layers for MR Brain Segmentation. 394-403
Computational Precision Medicine
- Alexandre Momeni, Marc Thibault, Olivier Gevaert:
Dropout-Enabled Ensemble Learning for Multi-scale Biomedical Data. 407-415 - Aditya Bagari, Ashish Kumar, Avinash Kori, Mahendra Khened, Ganapathy Krishnamurthi:
A Combined Radio-Histological Approach for Classification of Low Grade Gliomas. 416-427 - Xinpeng Xie, Yuexiang Li, Menglu Zhang, Linlin Shen:
Robust Segmentation of Nucleus in Histopathology Images via Mask R-CNN. 428-436
Stroke Workshop on Imaging and Treatment Challenges
- David Robben, Paul Suetens:
Perfusion Parameter Estimation Using Neural Networks and Data Augmentation. 439-446 - Andreas Hess, Raphael Meier, Johannes Kaesmacher, Simon Jung, Fabien Scalzo, David S. Liebeskind, Roland Wiest, Richard McKinley:
Synthetic Perfusion Maps: Imaging Perfusion Deficits in DSC-MRI with Deep Learning. 447-455 - Mobarakol Islam, Parita Sanghani, Angela An Qi See, Michael Lucas James, Nicolas Kon Kam King, Hongliang Ren:
ICHNet: Intracerebral Hemorrhage (ICH) Segmentation Using Deep Learning. 456-463 - Lorenza Brusini, Ilaria Boscolo Galazzo, Mauro Zucchelli, Cristina Granziera, Gloria Menegaz:
Can Diffusion MRI Reveal Stroke-Induced Microstructural Changes in GM? 464-471
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