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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 II

  • Conference proceedings
  • © 2019

Overview

Editors:
  1. Alessandro Crimi

    1. University Hospital of Zurich, Zürich, Switzerland

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  2. Spyridon Bakas

    1. University of Pennsylvania, Philadelphia, USA

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  3. Hugo Kuijf

    1. University Medical Center Utrecht, Utrecht, The Netherlands

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  4. Farahani Keyvan

    1. National Cancer Institute, Bethesda, USA

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  5. Mauricio Reyes

    1. University of Bern, Bern, Switzerland

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  6. Theo van Walsum

    1. Erasmus University Medical Center, Rotterdam, The Netherlands

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11384)

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 2018.

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Table of contents (45 papers)

  1. Front Matter

    Pages I-XXI
    Download chapter PDF

  2. Brain Tumor Image Segmentation

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Segmentation of Brain Tumors and Patient Survival Prediction: Methods for the BraTS 2018 Challenge

      • Leon Weninger, Oliver Rippel, Simon Koppers, Dorit Merhof
      Pages 3-12

    3. Segmenting Brain Tumors from MRI Using Cascaded Multi-modal U-Nets

      • Michal Marcinkiewicz, Jakub Nalepa, Pablo Ribalta Lorenzo, Wojciech Dudzik, Grzegorz Mrukwa
      Pages 13-24

    4. Automatic Brain Tumor Segmentation by Exploring the Multi-modality Complementary Information and Cascaded 3D Lightweight CNNs

      • Jun Ma, Xiaoping Yang
      Pages 25-36

    5. Deep Convolutional Neural Networks Using U-Net for Automatic Brain Tumor Segmentation in Multimodal MRI Volumes

      • Adel Kermi, Issam Mahmoudi, Mohamed Tarek Khadir
      Pages 37-48

    6. Multimodal Brain Tumor Segmentation Using Cascaded V-Nets

      • Rui Hua, Quan Huo, Yaozong Gao, Yu Sun, Feng Shi
      Pages 49-60

    7. Automatic Brain Tumor Segmentation Using Convolutional Neural Networks with Test-Time Augmentation

      • Guotai Wang, Wenqi Li, Sébastien Ourselin, Tom Vercauteren
      Pages 61-72

    8. Extending 2D Deep Learning Architectures to 3D Image Segmentation Problems

      • Alberto Albiol, Antonio Albiol, Francisco Albiol
      Pages 73-82

    9. Tumor Segmentation and Survival Prediction in Glioma with Deep Learning

      • Li Sun, Songtao Zhang, Lin Luo
      Pages 83-93

    10. Multi-planar Spatial-ConvNet for Segmentation and Survival Prediction in Brain Cancer

      • Subhashis Banerjee, Sushmita Mitra, B. Uma Shankar
      Pages 94-104

    11. A Pretrained DenseNet Encoder for Brain Tumor Segmentation

      • Jean Stawiaski
      Pages 105-115

    12. Hierarchical Multi-class Segmentation of Glioma Images Using Networks with Multi-level Activation Function

      • Xiaobin Hu, Hongwei Li, Yu Zhao, Chao Dong, Bjoern H. Menze, Marie Piraud
      Pages 116-127

    13. Brain Tumor Segmentation and Tractographic Feature Extraction from Structural MR Images for Overall Survival Prediction

      • Po-Yu Kao, Thuyen Ngo, Angela Zhang, Jefferson W. Chen, B. S. Manjunath
      Pages 128-141

    14. Glioma Prognosis: Segmentation of the Tumor and Survival Prediction Using Shape, Geometric and Clinical Information

      • Mobarakol Islam, V. Jeya Maria Jose, Hongliang Ren
      Pages 142-153

    15. Segmentation of Brain Tumors Using DeepLabv3+

      • Ahana Roy Choudhury, Rami Vanguri, Sachin R. Jambawalikar, Piyush Kumar
      Pages 154-167

    16. Brain Tumor Segmentation on Multimodal MR Imaging Using Multi-level Upsampling in Decoder

      • Yan Hu, Xiang Liu, Xin Wen, Chen Niu, Yong Xia
      Pages 168-177

    17. Neuromorphic Neural Network for Multimodal Brain Image Segmentation and Overall Survival Analysis

      • Woo-Sup Han, Il Song Han
      Pages 178-188

    18. Glioma Segmentation with Cascaded UNet

      • Dmitry Lachinov, Evgeny Vasiliev, Vadim Turlapov
      Pages 189-198

    19. Segmentation of Gliomas and Prediction of Patient Overall Survival: A Simple and Fast Procedure

      • Elodie Puybareau, Guillaume Tochon, Joseph Chazalon, Jonathan Fabrizio
      Pages 199-209
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Other volumes

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

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

Keywords

About this book

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.

Editors and Affiliations

  • University Hospital of Zurich, Zürich, Switzerland

    Alessandro Crimi

  • University of Pennsylvania, Philadelphia, USA

    Spyridon Bakas

  • University Medical Center Utrecht, Utrecht, The Netherlands

    Hugo Kuijf

  • National Cancer Institute, Bethesda, USA

    Farahani Keyvan

  • University of Bern, Bern, Switzerland

    Mauricio Reyes

  • Erasmus University Medical Center, Rotterdam, The Netherlands

    Theo van Walsum

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