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

8th International Workshop, BrainLes 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Revised Selected Papers, Part I

  • Conference proceedings
  • © 2023

Overview

Editors:
  1. Spyridon Bakas

    1. University of Pennsylvania, Philadelphia, USA

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  2. Alessandro Crimi

    1. Sano, Center for Computational Personalised Medicine, Kraków, Poland

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  3. Ujjwal Baid

    1. University of Pennsylvania, Philadelphia, USA

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  4. Sylwia Malec

    1. Sano, Center for Computational Personalised Medicine, Kraków, Poland

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  5. Monika Pytlarz

    1. Sano, Center for Computational Personalised Medicine, Kraków, Poland

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  6. Bhakti Baheti

    1. University of Pennsylvania, Philadelphia, USA

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  7. Maximilian Zenk

    1. German Cancer Research Center, Heidelberg, Germany

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  8. Reuben Dorent

    1. Harvard Medical School, Boston, USA

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 13769)

Included in the following conference series:

Conference proceedings info: BrainLes 2022.

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About this book

This book constitutes the refereed proceedings of the 8th International MICCAI Brainlesion Workshop, BrainLes 2022, as well as the Brain Tumor Segmentation (BraTS) Challenge, the Brain Tumor Sequence Registration (BraTS-Reg) Challenge, the Cross-Modality Domain Adaptation (CrossMoDA) Challenge, and the Federated Tumor Segmentation (FeTS) Challenge. These were held jointly at the Medical Image Computing for Computer Assisted Intervention Conference, MICCAI 2022, in September 2022. The 46 revised full papers presented in these volumes were selected form 65 submissions.The presented contributions describe the research of computational scientists and clinical researchers working on brain lesions - specifically glioma, multiple sclerosis, cerebral stroke, traumatic brain injuries, vestibular schwannoma, and white matter hyper-intensities of presumed vascular origin. 

Keywords

Table of contents (24 papers)

  1. Front Matter

    Pages i-xix
    Download chapter PDF

  2. BrainLes

    1. Front Matter

      Pages 1-1
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    2. Deep Quality Estimation: Creating Surrogate Models for Human Quality Ratings

      • Florian Kofler, Ivan Ezhov, Lucas Fidon, Izabela Horvath, Ezequiel de la Rosa, John LaMaster et al.
      Pages 3-13

    3. Unsupervised Anomaly Localization with Structural Feature-Autoencoders

      • Felix Meissen, Johannes Paetzold, Georgios Kaissis, Daniel Rueckert
      Pages 14-24

    4. Transformer Based Models for Unsupervised Anomaly Segmentation in Brain MR Images

      • Ahmed Ghorbel, Ahmed Aldahdooh, Shadi Albarqouni, Wassim Hamidouche
      Pages 25-44

    5. Weighting Schemes for Federated Learning in Heterogeneous and Imbalanced Segmentation Datasets

      • Sebastian Otálora, Jonathan Rafael-Patiño, Antoine Madrona, Elda Fischi-Gomez, Veronica Ravano, Tobias Kober et al.
      Pages 45-56

    6. Temporally Adjustable Longitudinal Fluid-Attenuated Inversion Recovery MRI Estimation / Synthesis for Multiple Sclerosis

      • Jueqi Wang, Derek Berger, Erin Mazerolle, Othman Soufan, Jacob Levman
      Pages 57-67

    7. Leveraging 2D Deep Learning ImageNet-trained Models for Native 3D Medical Image Analysis

      • Bhakti Baheti, Sarthak Pati, Bjoern Menze, Spyridon Bakas
      Pages 68-79

    8. Probabilistic Tissue Mapping for Tumor Segmentation and Infiltration Detection of Glioma

      • Selene De Sutter, Wietse Geens, Matías Bossa, Anne-Marie Vanbinst, Johnny Duerinck, Jef Vandemeulebroucke
      Pages 80-89

    9. Robustifying Automatic Assessment of Brain Tumor Progression from MRI

      • Krzysztof Kotowski, Bartosz Machura, Jakub Nalepa
      Pages 90-101

    10. MidFusNet: Mid-dense Fusion Network for Multi-modal Brain MRI Segmentation

      • Wenting Duan, Lei Zhang, Jordan Colman, Giosue Gulli, Xujiong Ye
      Pages 102-114

    11. Semi-supervised Intracranial Aneurysm Segmentation with Selected Unlabeled Data

      • Shiyu Lu, Hao Wang, Chuyang Ye
      Pages 115-123

  3. BraTS

    1. Front Matter

      Pages 125-125
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    2. Multimodal CNN Networks for Brain Tumor Segmentation in MRI: A BraTS 2022 Challenge Solution

      • Ramy A. Zeineldin, Mohamed E. Karar, Oliver Burgert, Franziska Mathis-Ullrich
      Pages 127-137

    3. Multi-modal Transformer for Brain Tumor Segmentation

      • Jihoon Cho, Jinah Park
      Pages 138-148

    4. An Efficient Cascade of U-Net-Like Convolutional Neural Networks Devoted to Brain Tumor Segmentation

      • Philippe Bouchet, Jean-Baptiste Deloges, Hugo Canton-Bacara, Gaëtan Pusel, Lucas Pinot, Othman Elbaz et al.
      Pages 149-161

    5. Tuning U-Net for Brain Tumor Segmentation

      • Michał Futrega, Michał Marcinkiewicz, Pablo Ribalta
      Pages 162-173

    6. Diffraction Block in Extended nn-UNet for Brain Tumor Segmentation

      • Qingfan Hou, Zhuofei Wang, Jiao Wang, Jian Jiang, Yanjun Peng
      Pages 174-185

    7. Infusing Domain Knowledge into nnU-Nets for Segmenting Brain Tumors in MRI

      • Krzysztof Kotowski, Szymon Adamski, Bartosz Machura, Lukasz Zarudzki, Jakub Nalepa
      Pages 186-194

    8. Multi-modal Brain Tumour Segmentation Using Transformer with Optimal Patch Size

      • Ramtin Mojtahedi, Mohammad Hamghalam, Amber L. Simpson
      Pages 195-204
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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

Editors and Affiliations

  • University of Pennsylvania, Philadelphia, USA

    Spyridon Bakas, Ujjwal Baid, Bhakti Baheti

  • Sano, Center for Computational Personalised Medicine, Kraków, Poland

    Alessandro Crimi, Monika Pytlarz

  • Sano, Center for Computational Personalised Medicine, Kraków, Poland

    Sylwia Malec

  • German Cancer Research Center, Heidelberg, Germany

    Maximilian Zenk

  • Harvard Medical School, Boston, USA

    Reuben Dorent

Bibliographic Information

  • Book Title: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries

  • Book Subtitle: 8th International Workshop, BrainLes 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Revised Selected Papers, Part I

  • Editors: Spyridon Bakas, Alessandro Crimi, Ujjwal Baid, Sylwia Malec, Monika Pytlarz, Bhakti Baheti, Maximilian Zenk, … Reuben Dorent

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-031-33842-7

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023

  • Softcover ISBN: 978-3-031-33841-0Published: 18 July 2023

  • eBook ISBN: 978-3-031-33842-7Published: 17 July 2023

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XIX, 285

  • Number of Illustrations: 15 b/w illustrations, 86 illustrations in colour

  • Topics: Image Processing and Computer Vision, Health Informatics, Computer Applications, Computers and Education, Artificial Intelligence, Artificial Intelligence

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