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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

  • Conference proceedings
  • © 2016

Overview

Editors:
  1. Alessandro Crimi

    1. Istituto Italiano di Tecnologia (IIT), Genova, Italy

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  2. Bjoern Menze

    1. TU München, Computer Science, München, Germany

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  3. Oskar Maier

    1. Medical Informatics, University of Lübeck, Lübeck, Germany

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  4. Mauricio Reyes

    1. Surgical Technology and Biomechanics, Universität Bern, Bern, Switzerland

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  5. Heinz Handels

    1. Medical Informatics, University of Lübeck, Lübeck, Germany

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 9556)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

Included in the following conference series:

Conference proceedings info: BrainLes 2015.

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Table of contents (25 papers)

  1. Front Matter

    Pages I-IX
    Download chapter PDF

  2. Brain Lesions, Introduction

    • Alessandro Crimi
    Pages 1-5

  3. Brain Lesion Image Analysis

    1. Front Matter

      Pages 7-7
      Download chapter PDF

    2. Simultaneous Whole-Brain Segmentation and White Matter Lesion Detection Using Contrast-Adaptive Probabilistic Models

      • Oula Puonti, Koen Van Leemput
      Pages 9-20

    3. Stroke Lesion Segmentation Using a Probabilistic Atlas of Cerebral Vascular Territories

      • Alexandra Derntl, Claudia Plant, Philipp Gruber, Susanne Wegener, Jan S. Bauer, Bjoern H. Menze
      Pages 21-32

    4. Fiber Tracking in Traumatic Brain Injury: Comparison of 9 Tractography Algorithms

      • Emily L. Dennis, Gautam Prasad, Madelaine Daianu, Liang Zhan, Talin Babikian, Claudia Kernan et al.
      Pages 33-44

    5. Combining Unsupervised and Supervised Methods for Lesion Segmentation

      • Tim Jerman, Alfiia Galimzianova, Franjo Pernuš, Boštjan Likar, Žiga Špiclin
      Pages 45-56

    6. Assessment of Tissue Injury in Severe Brain Trauma

      • Christophe Maggia, Senan Doyle, Florence Forbes, Olivier Heck, Irène Troprès, Corentin Berthet et al.
      Pages 57-68

    7. A Nonparametric Growth Model for Brain Tumor Segmentation in Longitudinal MR Sequences

      • Esther Alberts, Guillaume Charpiat, Yuliya Tarabalka, Thomas Huber, Marc-André Weber, Jan Bauer et al.
      Pages 69-79

    8. A Semi-automatic Method for Segmentation of Multiple Sclerosis Lesions on Dual-Echo Magnetic Resonance Images

      • Loredana Storelli, Elisabetta Pagani, Maria Assunta Rocca, Mark A. Horsfield, Massimo Filippi
      Pages 80-90

    9. Bayesian Stroke Lesion Estimation for Automatic Registration of DTI Images

      • Félix Renard, Matthieu Urvoy, Assia Jaillard
      Pages 91-103

    10. A Quantitative Approach to Characterize MR Contrasts with Histology

      • Yaël Balbastre, Michel E. Vandenberghe, Anne-Sophie Hérard, Pauline Gipchtein, Caroline Jan, Anselme L. Perrier et al.
      Pages 104-115

  4. Brain Tumor Image Segmentation

    1. Front Matter

      Pages 117-117
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    2. Image Features for Brain Lesion Segmentation Using Random Forests

      • Oskar Maier, Matthias Wilms, Heinz Handels
      Pages 119-130

    3. Deep Convolutional Neural Networks for the Segmentation of Gliomas in Multi-sequence MRI

      • Sérgio Pereira, Adriano Pinto, Victor Alves, Carlos A. Silva
      Pages 131-143

    4. GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation

      • Spyridon Bakas, Ke Zeng, Aristeidis Sotiras, Saima Rathore, Hamed Akbari, Bilwaj Gaonkar et al.
      Pages 144-155

    5. Parameter Learning for CRF-Based Tissue Segmentation of Brain Tumors

      • Raphael Meier, Venetia Karamitsou, Simon Habegger, Roland Wiest, Mauricio Reyes
      Pages 156-167

    6. Brain Tumor Segmentation Using a Generative Model with an RBM Prior on Tumor Shape

      • Mikael Agn, Oula Puonti, Per Munck af Rosenschöld, Ian Law, Koen Van Leemput
      Pages 168-180

    7. Multi-modal Brain Tumor Segmentation Using Stacked Denoising Autoencoders

      • Kiran Vaidhya, Subramaniam Thirunavukkarasu, Varghese Alex, Ganapathy Krishnamurthi
      Pages 181-194

    8. A Convolutional Neural Network Approach to Brain Tumor Segmentation

      • Mohammad Havaei, Francis Dutil, Chris Pal, Hugo Larochelle, Pierre-Marc Jodoin
      Pages 195-208
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Other volumes

  1. Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries

Keywords

About this book

This book constitutes the thoroughly refereed post-workshop proceedings of the International Workshop on Brain Lesion (BrainLes), Brain Tumor Segmentation (BRATS) and Ischemic Stroke Lesion Segmentation (ISLES), held in Munich, Germany, on October 5, 2015, in conjunction with the International Conference on Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015.

The 25 papers presented in this volume were carefully reviewed and selected from 28 submissions. They are grouped around the following topics: brain lesion image analysis; brain tumor image segmentation; ischemic stroke lesion image segmentation.

Editors and Affiliations

  • Istituto Italiano di Tecnologia (IIT), Genova, Italy

    Alessandro Crimi

  • TU München, Computer Science, München, Germany

    Bjoern Menze

  • Medical Informatics, University of Lübeck, Lübeck, Germany

    Oskar Maier, Heinz Handels

  • Surgical Technology and Biomechanics, Universität Bern, Bern, Switzerland

    Mauricio Reyes

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