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Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 Workshops

LDTM 2024, MMMI/ML4MHD 2024, ML-CDS 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6–10, 2024, Proceedings

  • Conference proceedings
  • © 2025

Overview

Editors:
  1. Anna Schroder

    1. University College London, London, UK

  2. Xiang Li

    1. Massachusetts General Hospital, Somerville, USA

  3. Tanveer Syeda-Mahmood

    1. IBM Almaden Research Center, San Jose, USA

  4. Neil P. Oxtoby

    1. University College London, London, UK

  5. Alexandra Young

    1. University College London, London, UK

  6. Alessa Hering

    1. Radboud University Medical Center, Nijmegen, The Netherlands

  7. Tejas S. Mathai

    1. National Institutes of Health, Bethesda, USA

  8. Pritam Mukherjee

    1. National Institutes of Health, Bethesda, USA

  9. Sven Kuckertz

    1. Fraunhofer MEVIS, Lübeck, Germany

  10. Tiantian He

    1. University College London, London, UK

  11. Isaac Llorente-Saguer

    1. University College London, London, UK

  12. Andreas Maier

    1. Friedrich-Alexander-Universität Erlangen-Nuremberg, Erlangen, Germany

  13. Satyananda Kashyap

    1. IBM Research, San Jose, USA

  14. Hayit Greenspan

    1. Mount Sinai Hospital, New York, USA

  15. Anant Madabhushi

    1. Emory University, Atlanta, USA

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 15401)

Included in the following conference series:

Conference proceedings info: MICCAI 2024.

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About this book

This book constitutes the proceedings from the workshops LDTM 2024, MMMI/ML4MHD 2024, and ML-CDS 2024 which were held in conjunction with the 27th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2024, in Marrakesh, Morocco, in October 2024.

The papers included in this book stem from the following workshops:

- LDTM 2024, Workshop on Longitudinal Disease Tracking and Modeling with Medical Images and Data, which accepted 13 papers from 15 submissions. 

- MMMI/ML4MHD 2024, the 5th International Workshop on Multiscale Multimodal Medical Imaging, MMMI 2024, and the  First Workshop on Machine Learning for Multimodal/-sensor Healthcare Data, ML4MHD2024, from which 8 papers are included from a total of 14 submissions to the workshop

- ML-CDS 2024, Workshop on Multimodal Learning and Fusion Across Scales for Clinical Decision Support, which accepted 4 papers out of 5 submissions

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Table of contents (21 papers)

  1. Front Matter

    Pages i-xix
    Download chapter PDF

  2. LDTM Workshop

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Disease Progression Modelling and Stratification for Detecting Sub-trajectories in the Natural History of Pathologies: Application to Parkinson’s Disease Trajectory Modelling

      • Alessandro Viani, Boris A. Gutman, Emile d’Angremont, Marco Lorenzi
      Pages 3-14

    3. Back to the Future: Challenges of Sparse and Irregular Medical Image Time Series

      • Nico Albert Disch, Robin Peretzke, Saikat Roy, Constantin Ulrich, David Zimmerer, Rainer Stiefelhagen et al.
      Pages 15-25

    4. Individualized Multi-horizon MRI Trajectory Prediction for Alzheimer’s Disease

      • Rosemary He, Gabriella Ang, Daniel Tward, for the Alzheimer’s Disease Neuroimaging Initiative
      Pages 26-37

    5. Towards Longitudinal Characterization of Multiple Sclerosis Atrophy Employing SynthSeg Framework and Normative Modeling

      • Pedro M. Gordaliza, Nataliia Molchanova, Maxence Wynen, Pietro Maggi, Alessandro Cagol, Cristina Granziera et al.
      Pages 38-51

    6. SegHeD: Segmentation of Heterogeneous Data for Multiple Sclerosis Lesions with Anatomical Constraints

      • Berke Doga Basaran, Xinru Zhang, Paul M. Matthews, Wenjia Bai
      Pages 52-63

    7. Longitudinal Segmentation of MS Lesions via Temporal Difference Weighting

      • Maximilian R. Rokuss, Yannick Kirchhoff, Saikat Roy, Balint Kovacs, Constantin Ulrich, Tassilo Wald et al.
      Pages 64-74

    8. Registration of Longitudinal Liver Examinations for Tumor Progress Assessment

      • Walid Yassine, Martin Charachon, Céline Hudelot, Roberto Ardon
      Pages 75-87

    9. Tracking Lesion Evolution Using a Boundary Enhanced Approach for MS Change Segmentation (BEAMS)

      • Prateek Mathur, Brendan S. Kelly, Ronan P Killeen, Aonghus Lawlor
      Pages 88-100

    10. A Radiological-Based Coordinate System for the Human Body: A Proof-of-Concept

      • Teresa M. T. Bucho, Thierry N. Boellaard, Mateus Taveira, Zuhir Bodalal, Thi D. L. Nguyen-Kim, Regina Beets-Tan et al.
      Pages 101-110

  3. MMMI-ML4MHD Workshop

    1. Front Matter

      Pages 111-111
      Download chapter PDF

    2. Language Models Meet Anomaly Detection for Better Interpretability and Generalizability

      • Jun Li, Su Hwan Kim, Philip Müller, Lina Felsner, Daniel Rueckert, Benedikt Wiestler et al.
      Pages 113-123

    3. A Diffusion Model Embedded WCSAU-Net for 3D MRI Brain Tumor Segmentation

      • Zizhen Ji, Rui Chen, Pinyu Qiu, Xiaoyong Fu, Sheng Li, Jun Tan
      Pages 124-135

    4. Predicting Human Brain States with Transformer

      • Yifei Sun, Mariano Cabezas, Jiah Lee, Chenyu Wang, Wei Zhang, Fernando Calamante et al.
      Pages 136-146

    5. Cross-Modality Image Quality Prediction for Time-Resolved CT from Breathing Signals

      • Annette Schwarz, Jannis Dickmann, Christian Hofmann, Juliane Szkitsak, Christoph Bert, Andreas Maier et al.
      Pages 147-156

    6. RATNUS: Rapid, Automatic Thalamic Nuclei Segmentation Using Multimodal MRI Inputs

      • Anqi Feng, Zhangxing Bian, Blake E. Dewey, Alexa Gail Colinco, Jiachen Zhuo, Jerry L. Prince
      Pages 157-169

    7. HyperMM: Robust Multimodal Learning with Varying-Sized Inputs

      • Hava Chaptoukaev, Vincenzo Marcianó, Francesco Galati, Maria A. Zuluaga
      Pages 170-183

    8. HEMIT: H&E to Multiplex-Immunohistochemistry Image Translation with Dual-Branch Pix2pix Generator

      • Chang Bian, Beth Phillips, Tim Cootes, Martin Fergie
      Pages 184-197

    9. Physics-Informed Latent Diffusion for Multimodal Brain MRI Synthesis

      • Sven Lüpke, Yousef Yeganeh, Ehsan Adeli, Nassir Navab, Azade Farshad
      Pages 198-207
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Editors and Affiliations

  • University College London, London, UK

    Anna Schroder, Neil P. Oxtoby, Alexandra Young, Tiantian He, Isaac Llorente-Saguer

  • Massachusetts General Hospital, Somerville, USA

    Xiang Li

  • IBM Almaden Research Center, San Jose, USA

    Tanveer Syeda-Mahmood

  • Radboud University Medical Center, Nijmegen, The Netherlands

    Alessa Hering

  • National Institutes of Health, Bethesda, USA

    Tejas S. Mathai, Pritam Mukherjee

  • Fraunhofer MEVIS, Lübeck, Germany

    Sven Kuckertz

  • Friedrich-Alexander-Universität Erlangen-Nuremberg, Erlangen, Germany

    Andreas Maier

  • IBM Research, San Jose, USA

    Satyananda Kashyap

  • Mount Sinai Hospital, New York, USA

    Hayit Greenspan

  • Emory University, Atlanta, USA

    Anant Madabhushi

Accessibility Information

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Bibliographic Information

  • Book Title: Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 Workshops

  • Book Subtitle: LDTM 2024, MMMI/ML4MHD 2024, ML-CDS 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6–10, 2024, Proceedings

  • Editors: Anna Schroder, Xiang Li, Tanveer Syeda-Mahmood, Neil P. Oxtoby, Alexandra Young, Alessa Hering, Tejas S. Mathai, Pritam Mukherjee, Sven Kuckertz, Tiantian He, Isaac Llorente-Saguer, Andreas Maier, Satyananda Kashyap, Hayit Greenspan, … Anant Madabhushi

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-031-84525-3

  • 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 2025

  • Softcover ISBN: 978-3-031-84524-6Published: 13 April 2025

  • eBook ISBN: 978-3-031-84525-3Published: 12 April 2025

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XIX, 262

  • Number of Illustrations: 4 b/w illustrations, 95 illustrations in colour

  • Topics: Computer Imaging, Vision, Pattern Recognition and Graphics

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