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Data Engineering in Medical Imaging

Third MICCAI Workshop, DEMI 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 27, 2025, Proceedings

  • Conference proceedings
  • © 2026

Overview

Editors:
  1. Binod Bhattarai

    1. University of Aberdeen, Aberdeen, UK

  2. Anita Rau

    1. Stanford University, Stanford, USA

  3. Razvan Caramalau

    1. Medtronic Digital Technologies, London, UK

  4. Annika Reinke

    1. German Cancer Research Institute, Heidelberg, Germany

  5. Anh Nguyen

    1. University of Liverpool, Liverpool, UK

  6. Ana Namburete

    1. University of Oxford, Oxford, UK

  7. Prashnna Gyawali

    1. West Virginia University, Morgantown, USA

  8. Danail Stoyanov

    1. University College London, London, UK

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 16191)

Included in the following conference series:

Conference proceedings info: DEMI 2025.

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About this book

This book constitutes the proceedings of the Third MICCAI Workshop on Data Engineering in Medical Imaging, DEMI 2025, held in conjunction with the 28th International conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2025, in Daejeon, South Korea, on September 27, 2025.

The 24 full papers included in this book were carefully reviewed and selected from 33 submissions. These papers focus on the topic of data engineering in medical imaging and address open questions in the field. The workshop welcomes various approaches such as data and label augmentation, active learning and active synthesis, federated learning, multimodal learning, self-supervised learning, and large-scale data management and data quality assessment.

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Table of contents (24 papers)

  1. Front Matter

    Pages i-xi
    Download chapter PDF

  2. Surgical Vision World Model

    • Saurabh Koju, Saurav Bastola, Prashant Shrestha, Sanskar Amgain, Yash Raj Shrestha, Rudra P. K. Poudel et al.
    Pages 1-10

  3. Overcoming Data Scarcity: Brain Tumor Segmentation in Pediatric and African Populations

    • Abdulkhalek Al-Fakih, Abbas Mohamed Rezk, Abdullah Shazly, Kanghyun Ryu, Mohammed A. Al-masni
    Pages 11-20

  4. PiMPiC: An Overlap-Aware Contrastive Learning Framework for 3D Patch-Based Medical Image Segmentation

    • Reza Karimzadeh, Ehsan Yousefzadeh-Asl-Miandoab, Hossein Arabi, Pinar Tözün, Bulat Ibragimov
    Pages 21-31

  5. DiffusionXRay: A Diffusion and GAN-Based Approach for Enhancing Digitally Reconstructed Chest Radiographs

    • Aryan Goyal, Ashish Mittal, Pranav Rao, Manoj Tadepalli, Preetham Putha
    Pages 32-41

  6. SingleStrip: Learning Skull-Stripping from a Single Labeled Example

    • Bella Specktor-Fadida, Malte Hoffmann
    Pages 42-52

  7. Kvasir-VQA-x1:A Multimodal Dataset for Medical Reasoning and Robust MedVQA in Gastrointestinal Endoscopy

    • Sushant Gautam, Michael Riegler, Pål Halvorsen
    Pages 53-63

  8. Do Edges Matter? Investigating Edge-Enhanced Pre-training for Medical Image Segmentation

    • Paul Zaha, Simeon Allmendinger, Lars Böcking, Leopold Müller, Niklas Kühl
    Pages 64-74

  9. Enhancing Malaria-Infected Red Blood Cell Detection with Domain-Aware Generative Augmentation

    • Luis F. Fraga, Adam Balint, Yongjoon Hwang
    Pages 75-84

  10. Analysis of Transferability Estimation Metrics for Surgical Phase Recognition

    • Prabhant Singh, Yiping Li, Yasmina Al Khalil
    Pages 85-94

  11. Expert-Guided Explainable Few-Shot Learning for Medical Image Diagnosis

    • Ifrat Ikhtear Uddin, Longwei Wang, KC Santosh
    Pages 95-104

  12. Lesion-Aware Visual-Language Fusion for Automated Image Captioning of Ulcerative Colitis Endoscopic Examinations

    • Alexis Iván López Escamilla, Gilberto Ochoa, Sharib Ali
    Pages 105-114

  13. Zero-Shot Monocular Metric Depth for Endoscopic Images

    • Nicolas Toussaint, Emanuele Colleoni, Ricardo Sanchez-Matilla, Joshua Sutcliffe, Vanessa Thompson, Muhammad Asad et al.
    Pages 115-124

  14. Robust Federated Anomaly Detection Using Dual-Signal Autoencoders: Application to Kidney Stone Identification in Ureteroscopy

    • Ivan Reyes-Amezcua, Francisco Lopez-Tiro, Clément Larose, Christian Daul, Andres Mendez-Vazquez, Gilberto Ochoa-Ruiz
    Pages 125-135

  15. Rad-Surf: Automated Synthesis of Radiographs and Vertebral Surfaces for Single-View Reconstruction

    • R. Neeraja, A. Anusha, Vivek Maik, Aparna Purayath, Manojkumar Lakshmanan, Mohanasankar Sivaprakasam
    Pages 136-146

  16. A Dataset and Benchmark for Enhancing Retained Foreign Object Detection Through Physics-Based Image Synthesis

    • Liwei Zhou, Yuli Wang, Victoria Shi, Jonathan Feng, Lin-mei Zhao, Norman Atagu et al.
    Pages 147-156

  17. Unmasking Interstitial Lung Diseases: Leveraging Masked Autoencoders for Diagnosis

    • Ethan Dack, Lorenzo Brigato, Vasilis Dedousis, Janine Gote-Schniering, Cheryl Magnin, Hanno Hoppe et al.
    Pages 157-167

  18. Robust Early Detection of Barrett’s Neoplasia: Addressing Low-Prevalence Challenges with Generative Modeling

    • Tim J. M. Jaspers, Francisco Caetano, Cris H. B. Claessens, Carolus H. J. Kusters, Haiko Middeljans, Martijn R. Jong et al.
    Pages 168-179

  19. Instance-Balanced Patch Sampling for Whole-Body Lesion Segmentation

    • Joris Wuts, Jakub Ceranka, Jef Vandemeulebroucke, Frédéric Lecouvet
    Pages 180-189

  20. Calibrated Self-supervised Vision Transformers Improve Intracranial Arterial Calcification Segmentation from Clinical CT Head Scans

    • Benjamin Jin, Grant Mair, Joanna M. Wardlaw, Maria del C. Valdés Hernández
    Pages 190-200
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Other volumes

  1. Data Engineering in Medical Imaging

Editors and Affiliations

  • University of Aberdeen, Aberdeen, UK

    Binod Bhattarai

  • Stanford University, Stanford, USA

    Anita Rau

  • Medtronic Digital Technologies, London, UK

    Razvan Caramalau

  • German Cancer Research Institute, Heidelberg, Germany

    Annika Reinke

  • University of Liverpool, Liverpool, UK

    Anh Nguyen

  • University of Oxford, Oxford, UK

    Ana Namburete

  • West Virginia University, Morgantown, USA

    Prashnna Gyawali

  • University College London, London, UK

    Danail Stoyanov

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Bibliographic Information

  • Book Title: Data Engineering in Medical Imaging

  • Book Subtitle: Third MICCAI Workshop, DEMI 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 27, 2025, Proceedings

  • Editors: Binod Bhattarai, Anita Rau, Razvan Caramalau, Annika Reinke, Anh Nguyen, Ana Namburete, Prashnna Gyawali, … Danail Stoyanov

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-032-08009-7

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0), Springer Nature Proceedings Computer Science

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2026

  • Softcover ISBN: 978-3-032-08008-0Published: 12 October 2025

  • eBook ISBN: 978-3-032-08009-7Published: 11 October 2025

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XI, 257

  • Number of Illustrations: 4 b/w illustrations, 83 illustrations in colour

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

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