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ORCID1st Brainles@MICCAI 2015: Munich, Germany
- Alessandro Crimi, Bjoern H. Menze
, Oskar Maier, Mauricio Reyes, Heinz Handels:
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - First International Workshop, Brainles 2015, Held in Conjunction with MICCAI 2015, Munich, Germany, October 5, 2015, Revised Selected Papers. Lecture Notes in Computer Science 9556, Springer 2016, ISBN 978-3-319-30857-9 - Alessandro Crimi:
Brain Lesions, Introduction. 1-5
Brain Lesion Image Analysis
- Oula Puonti, Koen Van Leemput:
Simultaneous Whole-Brain Segmentation and White Matter Lesion Detection Using Contrast-Adaptive Probabilistic Models. 9-20 - Alexandra Derntl, Claudia Plant, Philipp Gruber, Susanne Wegener, Jan S. Bauer, Bjoern H. Menze:
Stroke Lesion Segmentation Using a Probabilistic Atlas of Cerebral Vascular Territories. 21-32 - Emily L. Dennis, Gautam Prasad, Madelaine Daianu, Liang Zhan, Talin Babikian, Claudia Kernan, Richard Mink, Christopher Babbitt, Jeffrey Johnson, Christopher C. Giza, Robert F. Asarnow, Paul M. Thompson:
Fiber Tracking in Traumatic Brain Injury: Comparison of 9 Tractography Algorithms. 33-44 - Tim Jerman, Alfiia Galimzianova, Franjo Pernus, Bostjan Likar, Ziga Spiclin:
Combining Unsupervised and Supervised Methods for Lesion Segmentation. 45-56 - Christophe Maggia, Senan Doyle, Florence Forbes, Olivier Heck, Irène Troprès, Corentin Berthet, Yann Teyssier, Lionel Velly, Jean-François Payen, Michel Dojat:
Assessment of Tissue Injury in Severe Brain Trauma. 57-68 - Esther Alberts, Guillaume Charpiat, Yuliya Tarabalka, Thomas Huber, Marc-André Weber, Jan S. Bauer, Claus Zimmer, Bjoern H. Menze:
A Nonparametric Growth Model for Brain Tumor Segmentation in Longitudinal MR Sequences. 69-79 - Loredana Storelli, Elisabetta Pagani, Maria Assunta Rocca, Mark A. Horsfield, Massimo Filippi:
A Semi-automatic Method for Segmentation of Multiple Sclerosis Lesions on Dual-Echo Magnetic Resonance Images. 80-90 - Félix Renard, Matthieu Urvoy, Assia Jaillard:
Bayesian Stroke Lesion Estimation for Automatic Registration of DTI Images. 91-103 - Yaël Balbastre, Michel E. Vandenberghe, Anne-Sophie Hérard, Pauline Gipchtein, Caroline Jan, Anselme L. Perrier, Philippe Hantraye, Romina Aron-Badin, Jean-François Mangin, Thierry Delzescaux:
A Quantitative Approach to Characterize MR Contrasts with Histology. 104-115
Brain Tumor Image Segmentation
- Oskar Maier, Matthias Wilms, Heinz Handels:
Image Features for Brain Lesion Segmentation Using Random Forests. 119-130 - Sérgio Pereira, Adriano Pinto, Victor Alves, Carlos A. Silva:
Deep Convolutional Neural Networks for the Segmentation of Gliomas in Multi-sequence MRI. 131-143 - Spyridon Bakas, Ke Zeng, Aristeidis Sotiras, Saima Rathore, Hamed Akbari, Bilwaj Gaonkar, Martin Rozycki, Sarthak Pati, Christos Davatzikos:
GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation. 144-155 - Raphael Meier, Venetia Karamitsou, Simon Habegger, Roland Wiest, Mauricio Reyes:
Parameter Learning for CRF-Based Tissue Segmentation of Brain Tumors. 156-167 - Mikael Agn, Oula Puonti, Per Munck af Rosenschöld, Ian Law, Koen Van Leemput:
Brain Tumor Segmentation Using a Generative Model with an RBM Prior on Tumor Shape. 168-180 - Kiran Vaidhya, Subramaniam Thirunavukkarasu, Alex Varghese, Ganapathy Krishnamurthi:
Multi-modal Brain Tumor Segmentation Using Stacked Denoising Autoencoders. 181-194 - Mohammad Havaei, Francis Dutil, Chris Pal, Hugo Larochelle, Pierre-Marc Jodoin:
A Convolutional Neural Network Approach to Brain Tumor Segmentation. 195-208
Ischemic Stroke Lesion Image Segmentation
- Hanna-Leena Halme, Antti Korvenoja, Eero Salli:
ISLES (SISS) Challenge 2015: Segmentation of Stroke Lesions Using Spatial Normalization, Random Forest Classification and Contextual Clustering. 211-221 - Ching-Wei Wang, Jia-Hong Lee:
Stroke Lesion Segmentation of 3D Brain MRI Using Multiple Random Forests and 3D Registration. 222-232 - Chaolu Feng, Dazhe Zhao, Min Huang:
Segmentation of Ischemic Stroke Lesions in Multi-spectral MR Images Using Weighting Suppressed FCM and Three Phase Level Set. 233-245 - Tom Haeck, Frederik Maes, Paul Suetens:
ISLES Challenge 2015: Automated Model-Based Segmentation of Ischemic Stroke in MR Images. 246-253 - David Robben, Daan Christiaens, Janaki Raman Rangarajan, Jaap Gelderblom, Philip Joris, Frederik Maes, Paul Suetens:
A Voxel-Wise, Cascaded Classification Approach to Ischemic Stroke Lesion Segmentation. 254-265 - Qaiser Mahmood, Abdul Basit:
Automatic Ischemic Stroke Lesion Segmentation in Multi-spectral MRI Images Using Random Forests Classifier. 266-274 - Richard McKinley, Levin Häni, Roland Wiest, Mauricio Reyes:
Segmenting the Ischemic Penumbra: A Decision Forest Approach with Automatic Threshold Finding. 275-283 - Michael Götz, Christian Weber, Christoph Kolb, Klaus H. Maier-Hein:
Input Data Adaptive Learning (IDAL) for Sub-acute Ischemic Stroke Lesion Segmentation. 284-295
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