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Cancer Prevention, Detection, and Intervention

Third MICCAI Workshop, CaPTion 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings

  • Conference proceedings
  • © 2025

Overview

Editors:
  1. Sharib Ali

    1. University of Leeds, Leeds, UK

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  2. Fons van der Sommen

    1. Eindhoven University of Technology, Eindhoven, The Netherlands

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  3. Bartłomiej Władysław Papież

    1. University of Oxford, Oxford, UK

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  4. Noha Ghatwary

    1. Arab Academy for Science and Technology, Giza, Egypt

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  5. Yueming Jin

    1. National University of Singapore, Singapore, Singapore

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  6. Iris Kolenbrander

    1. Eindhoven University of Technology, Eindhoven, The Netherlands

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 15199)

Included in the following conference series:

Conference proceedings info: CaPTion 2024.

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About this book

This book constitutes the refereed proceedings of the Third International Workshop on Cancer Prevention Through Early Detection, CaPTion, held in conjunction with the 27th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2024, in Marrakesh, Morocco, on October 6, 2024.

The 22 full papers presented in this book were carefully reviewed and selected from 25 submissions. They were organized in topical sections as follows: Classification and characterization; detection and segmentation; cancer/early cancer detection, treatment and survival prognosis.

Keywords

Table of contents (22 papers)

  1. Front Matter

    Pages i-xii
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  2. Classification and Characterization

    1. Front Matter

      Pages 1-1
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    2. Multi-center Ovarian Tumor Classification Using Hierarchical Transformer-Based Multiple-Instance Learning

      • Cris H.B. Claessens, Eloy W.R. Schultz, Anna Koch, Ingrid Nies, Terese A.E. Hellström, Joost Nederend et al.
      Pages 3-13

    3. FoTNet Enables Preoperative Differentiation of Malignant Brain Tumors with Deep Learning

      • Chenyi Hong, Hualiang Wang, Zhuoxuan Wu, Zuozhu Liu, Junhui Lv
      Pages 14-25

    4. Classification of Endoscopy and Video Capsule Images Using CNN-Transformer Model

      • Aliza Subedi, Smriti Regmi, Nisha Regmi, Bhumi Bhusal, Ulas Bagci, Debesh Jha
      Pages 26-36

    5. Multimodal Deep Learning-Based Prediction of Immune Checkpoint Inhibitor Efficacy in Brain Metastases

      • Tobias R. Bodenmann, Nelson Gil, Felix J. Dorfner, Mason C. Cleveland, Jay B. Patel, Shreyas Bhat Brahmavar et al.
      Pages 37-47

    6. Seeing More with Less: Meta-learning and Diffusion Models for Tumor Characterization in Low-Data Settings

      • Eva Pachetti, Sara Colantonio
      Pages 48-58

    7. Performance Evaluation of Deep Learning and Transformer Models Using Multimodal Data for Breast Cancer Classification

      • Sadam Hussain, Mansoor Ali, Usman Naseem, Beatriz Alejandra Bosques Palomo, Mario Alexis Monsivais Molina, Jorge Alberto Garza Abdala et al.
      Pages 59-69

  3. Detection and Segmentation

    1. Front Matter

      Pages 71-71
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    2. On Undesired Emergent Behaviors in Compound Prostate Cancer Detection Systems

      • Erlend Sortland Rolfsnes, Philip Thangngat, Trygve Eftestøl, Tobias Nordström, Fredrik Jäderling, Martin Eklund et al.
      Pages 73-82

    3. Optimizing Multi-expert Consensus for Classification and Precise Localization of Barrett’s Neoplasia

      • Carolus H. J. Kusters, Tim G. W. Boers, Tim J. M. Jaspers, Martijn R. Jong, Rixta A. H. van Eijck van Heslinga, Albert J. de Groof et al.
      Pages 83-92

    4. Automated Hepatocellular Carcinoma Analysis in Multi-phase CT with Deep Learning

      • Krzysztof Kotowski, Bartosz Machura, Damian Kucharski, Benjamín Gutiérrez-Becker, Agata Krason, Jean Tessier et al.
      Pages 93-103

    5. Refining Deep Learning Segmentation Maps with a Local Thresholding Approach: Application to Liver Surface Nodularity Quantification in CT

      • Sisi Yang, Alexandre Bône, Thomas Decaens, Joan Alexis Glaunes
      Pages 104-113

    6. Uncertainty-Aware Deep Learning Classification for MRI-Based Prostate Cancer Detection

      • Kamilia Taguelmimt, Hong-Phuong Dang, Gustavo Andrade Miranda, Dimitris Visvikis, Bernard Malavaud, Julien Bert
      Pages 114-123

    7. Generalized Polyp Detection from Colonoscopy Frames Using Proposed EDF-YOLO8 Network

      • Alyaa Amer, Alaa Hussein, Noushin Ahmadvand, Sahar Magdy, Abas Abdi, Nasim Dadashi Serej et al.
      Pages 124-132

    8. AI-Assisted Laryngeal Examination System

      • Chiara Baldini, Muhammad Adeel Azam, Madelaine Thorniley, Claudio Sampieri, Alessandro Ioppi, Giorgio Peretti et al.
      Pages 133-143

    9. UltraWeak: Enhancing Breast Ultrasound Cancer Detection with Deformable DETR and Weak Supervision

      • Ufaq Khan, Umair Nawaz, Abdulmotaleb E. Saddik
      Pages 144-153

    10. SelectiveKD: A Semi-supervised Framework for Cancer Detection in DBT Through Knowledge Distillation and Pseudo-labeling

      • Laurent Dillard, Hyeonsoo Lee, Weonsuk Lee, Tae Soo Kim, Ali Diba, Thijs Kooi
      Pages 154-163

  4. Cancer/Early Cancer Detection, Treatment, and Survival Prognosis

    1. Front Matter

      Pages 165-165
      Download chapter PDF

    2. AI Age Discrepancy: A Novel Parameter for Frailty Assessment in Kidney Tumor Patients

      • Rikhil Seshadri, Jayant Siva, Angelica Bartholomew, Clara Goebel, Gabriel Wallerstein-King, Beatriz López Morato et al.
      Pages 167-175
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Other volumes

  1. Cancer Prevention, Detection, and Intervention

Editors and Affiliations

  • University of Leeds, Leeds, UK

    Sharib Ali

  • Eindhoven University of Technology, Eindhoven, The Netherlands

    Fons van der Sommen, Iris Kolenbrander

  • University of Oxford, Oxford, UK

    Bartłomiej Władysław Papież

  • Arab Academy for Science and Technology, Giza, Egypt

    Noha Ghatwary

  • National University of Singapore, Singapore, Singapore

    Yueming Jin

Bibliographic Information

  • Book Title: Cancer Prevention, Detection, and Intervention

  • Book Subtitle: Third MICCAI Workshop, CaPTion 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings

  • Editors: Sharib Ali, Fons van der Sommen, Bartłomiej Władysław Papież, Noha Ghatwary, Yueming Jin, Iris Kolenbrander

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-031-73376-5

  • 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: 978-3-031-73375-8Published: 09 October 2024

  • eBook ISBN: 978-3-031-73376-5Published: 08 October 2024

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XII, 243

  • Number of Illustrations: 8 b/w illustrations, 61 illustrations in colour

  • Topics: Computer Imaging, Vision, Pattern Recognition and Graphics, Machine Learning, Computing Milieux, Computer Applications

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