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Emerging LLM/LMM Applications in Medical Imaging

First International Workshop, ELAMI 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 27, 2025, Proceedings

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  • © 2026
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Editors:
  1. Hien Van Nguyen

    1. University of Houston, Houston, USA

  2. Akash Awasthi

    1. University of Houston, Houston, USA

  3. Vishal M. Patel

    1. Johns Hopkins University, Baltimore, USA

  4. Ngan Le

    1. University of Arkansas, Fayetteville, USA

  5. Yuyin Zhou

    1. University of California, Santa Cruz, USA

  6. Sheng Liu

    1. Stanford University, Stanford, USA

  7. S. Kevin Zhou

    1. Chinese Academy of Sciences, Beijing, China

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 16146)

Included in the following conference series:

Conference proceedings info: ELAMI 2025.

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About this book

This book constitutes the proceedings of the First International Workshop on Emerging LLM/LMM Applications in Medical Imaging, ELAMI 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 27, 2025. 

The 14 full papers were carefully reviewed and selected from 24 submissions. The conference covers all aspects of Healthcare, LLM, LMM, Medical Imaging, AI, Machine learning, and Multimodal.

 

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Table of contents (14 papers)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. GMAT: Grounded Multi-agent Clinical Description Generation for Text Encoder in Vision-Language MIL for Whole Slide Image Classification

    • Ngoc Bui Lam Quang, Nam Le Nguyen Binh, Thanh-Huy Nguyen, Le Thien Phuc Nguyen, Quan Nguyen, Ulas Bagci
    Pages 1-9

  3. SCOPE: Label Extraction of Stroke Diagnosis from Unstructured Medical Reports Using Retrieval-Augmented Generation

    • Mumu Aktar, Gunjan Jindal, Salome Lou Bosshart, Alexander Stebner, Pedro Paiva, Mariana Bento et al.
    Pages 10-18

  4. Mind the Evaluation Gap: Large Language Models for Structured Data Extraction from Radiology Reports

    • Amirhossein Sabour, Kailin Chu, Mehrdad Eshraghi Dehaghani, Mehdi Moradi
    Pages 19-27

  5. NeuroReport-MS: Multi-scale Agentic AI for Automated Clinical Report Generation in Multiple Sclerosis

    • Khaoula Alaoui Belghiti, Nour Eddine Zekaoui, Mounia Mikram, Maryem Rhanoui
    Pages 28-35

  6. REMix: Refinement-Enhanced Visual-Textual Mixing for Lesion Segmentation

    • Soojin Hwang, Jaeyoon Sim, Won Hwa Kim
    Pages 36-44

  7. An LLM-Based Active Assistant and Smart Manual for CT Imaging Workflows

    • Zeinab Aliakbari Mamaghani, Linda Vorberg, Andreas Maier, Alexander Katzmann, Oliver Taubmann
    Pages 45-52

  8. SIGMA: Auto-Regressive VLM for Automated Radiology Report Generation from Longitudinal 3D CT Volumes

    • Khang C. Nguyen, Cheng Wang, Zong X. Shi, Yue Heng, Chuan Y. Qi, Masahiro Oda et al.
    Pages 53-61

  9. Specialised or Generic? Tokenization Choices for Radiology Language Models

    • Hermione Warr, Wentian Xu, Harry Anthony, Yasin Ibrahim, Daniel R. McGowan, Konstantinos Kamnitsas
    Pages 62-70

  10. SCOPE: Speech-Guided COllaborative PErception Framework for Surgical Scene Segmentation

    • Jecia Z. Y. Mao, Francis X. Creighton, Russell H. Taylor, Manish Sahu
    Pages 71-78

  11. Imagining Alternatives: Towards High-Resolution 3D Counterfactual Medical Image Generation via Language Guidance

    • Mohamed Mohamed, Brennan Nichyporuk, Douglas L. Arnold, Tal Arbel
    Pages 79-87

  12. Pixels Under Pressure: Exploring Fine-Tuning Paradigms for Foundation Models in High-Resolution Medical Imaging

    • Zahra TehraniNasab, Amar Kumar, Tal Arbel
    Pages 88-97

  13. DeepGPT-DILI: Integrating Graph Convolutional Networks and Large Language Model Embeddings for Accurate Drug-Induced Liver Injury Prediction

    • Minh Huu Nhat Le, Uyen Khoi Minh Huynh, Hong Xuan Ong, Phat K. Huynh, Minh-Toan Dinh, Han Hong Huynh et al.
    Pages 98-106

  14. From Reports to Relations: Large Language Models for Knowledge Graph Extraction in Digital Pathology

    • Karthik Prathaban, Farhan Akram, Stefan Klein, Martijn P. A. Starmans
    Pages 107-114

  15. 3D Vision–Language Models with Segmentation-Guided Multimodal Data for Spinal MRI Report Generation

    • Hoda Helmy, Abdullah Hosseini, Ahmed Ibrahim, Asfand Baig-Mirza, Ahmed-Ramadan Sadek, Ahmed Serag
    Pages 115-122

  16. Back Matter

    Pages 123-124
    Download chapter PDF
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Other volumes

  1. Emerging LLM/LMM Applications in Medical Imaging

Editors and Affiliations

  • University of Houston, Houston, USA

    Hien Van Nguyen, Akash Awasthi

  • Johns Hopkins University, Baltimore, USA

    Vishal M. Patel

  • University of Arkansas, Fayetteville, USA

    Ngan Le

  • University of California, Santa Cruz, USA

    Yuyin Zhou

  • Stanford University, Stanford, USA

    Sheng Liu

  • Chinese Academy of Sciences, Beijing, China

    S. Kevin Zhou

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Bibliographic Information

  • Book Title: Emerging LLM/LMM Applications in Medical Imaging

  • Book Subtitle: First International Workshop, ELAMI 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 27, 2025, Proceedings

  • Editors: Hien Van Nguyen, Akash Awasthi, Vishal M. Patel, Ngan Le, Yuyin Zhou, Sheng Liu, S. Kevin Zhou

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-032-07502-4

  • 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: 978-3-032-07501-7Published: 12 October 2025

  • eBook ISBN: 978-3-032-07502-4Published: 11 October 2025

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: X, 124

  • Number of Illustrations: 2 b/w illustrations, 25 illustrations in colour

  • Topics: Artificial Intelligence

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