THE 3RD MICCAI STUDENT BOARD (MSB) EMERGE WORKSHOP

📍 MSB EMERGE 26 will be held in-person on September 27, 2026 as a half-day satellite event of MICCAI 2026 in Strasbourg, France 🇫🇷

Overview

Fostering the Next Generation of Leaders in Medical Information Computing

🌟 What is EMERGE?

The MICCAI Student Board EMERGE Workshop, now in its third edition, is a platform dedicated to empowering early-career, student-led research within the MICCAI community. Building on the success of its inaugural year, EMERGE offers early-career researchers a unique opportunity to present and discuss their work, engage with senior researchers, and foster new collaborations in a mentorship-oriented and supportive setting.

Organized by students, for students, the workshop encourages independent research by supporting young investigators in their scientific and professional development. EMERGE provides an inclusive and supportive environment for students at all levels—undergraduate, master's, and doctoral—as well as recent graduates and early-career researchers to showcase their contributions to medical image computing and computer-assisted interventions. Presentations are designed to be mentorship- and constructive feedback–oriented, designed to provide constructive feedback from senior experts. The program includes keynotes by successful early-career researchers and career development talks tailored to young scientists.

Note: Young scientists as last authors preferred but not required. We also welcome joint co-last author, and first author papers by young scientists irrespective of last author status.

🎯 Why Attend?

  • Showcase your research at MICCAI 2026 in Strasbourg, France and gain visibility in the global medical imaging community
  • Receive expert feedback from senior MICCAI researchers through mentorship-oriented oral sessions
  • Network with peers, mentors and potential collaborators in a supportive setting
  • Enhance the visibility of your work through oral and poster presentations
  • Tailored keynotes and sessions for young scientists by the MICCAI Student Board
  • Opportunity to extend your work to MELBA – The Journal of Machine Learning for Biomedical Imaging

📝 Submission Categories

  • Archival Track: Full-length papers must present original research not published or under review elsewhere during the review period. Submissions will undergo double-blind peer review. Accepted papers will be published in Springer LNCS proceedings.
  • Non-Archival Track: Authors of accepted MICCAI 2026 (main conference) posters may present their work as an oral talk at EMERGE. These submissions will undergo a light, single-blind review for relevance and fit. The presenting author must be a young scientist.

🔬 Scientific Focus

The scope of the workshop covers medical image computing (MIC) and computer-assisted interventions (CAI), in line with the scientific goals of the MICCAI Society. We welcome original research that introduces new methods, applies existing techniques in novel ways, or provides in-depth analysis of medical imaging problems. Contributions may also include rigorous benchmarking or the release of new datasets that support the development and evaluation of medical imaging approaches.

This includes work on image formation, reconstruction, segmentation, diagnosis, and decision support. Studies combining imaging with clinical, molecular, or wearable data, or handling multimodal and longitudinal inputs, are also welcome. We encourage submissions focused on building reliable, fair, and generalizable AI systems, as well as solutions for personalized imaging, point-of-care use, and underserved populations. Topics such as surgical data science, robotic interventions, and teleradiology are of interest. Research targeting region-specific challenges—especially in the Pan-Asian context—is welcome and reflects this year’s special emphasis on the region. With growing interest in emerging areas such as foundation models and generative AI, we also invite submissions exploring their applications in medical imaging and computer-assisted interventions.

🏅 Awards and Publication Opportunities

  • The top three outstanding papers will be recognized at the awards ceremony and will receive $300, $200, and $100.
  • Accepted full papers will be published in the Springer LNCS MICCAI 2026 workshop proceedings.
  • Selected papers will be invited to submit extended versions to MELBA (The Journal of Machine Learning for Biomedical Imaging).
  • Accepted contributions will also be featured through our MICCAI Student Board social media channels to increase visibility and outreach.

Important Dates

All dates are in 23:59 Anywhere on Earth (AoE)

Call for papers April 7, 2026
Submission portal opens May 15, 2026
Paper submission due July 10, 2026
Reviews released to authors July 23, 2026
Rebuttals due July 29, 2026
Final decisions August 3, 2026
Camera-ready due August 12, 2026
Workshop day September 27, 2026

Submission

Submissions will undergo double-blind peer review and must follow these guidelines: a maximum of 8 pages for content (including figures and tables), with up to 2 additional pages for references. The paper template and formatting details can be found here. Submissions should follow the same guidelines and process as the MICCAI 2026 main conference.

Manuscripts must be submitted via the MSB EMERGE 2026 OpenReview submission portal.

Each submission will be reviewed by at least three reviewers. For accepted papers, official reviews are anonymous and publicly visible. Rebuttals and preprints will also be made publicly available on the OpenReview platform.

Keynote Speaker

Camila González

Dr. Camila González

Assistant Professor
Medical University of Vienna, Austria

Program

All times are local time in Strasbourg, France (CEST), on September 27, 2026.

Time Session
13:30 - 13:40 Opening Remarks and Introduction
13:40 - 14:05 Poster Teasers (20 × 1 min)
14:05 - 14:40 Oral Session 1: Multimodal & Generative Learning
  • GraM-Diff: A Unified Graph–Mamba Diffusion Framework for EEG-Based Alzheimer's Disease Data Generation and DiagnosisM. Sajid
  • Relational Learning of Temporal and Semantic Clinical Structured EHRs for Enhanced Patient Outcome ForecastingRahul Pal
  • MedHyperGraph: EHR-Integrated Multimodal Hyperedges for Clinical VQAHasan Md Tusfiqur Alam
14:40 - 15:15 Oral Session 2: Trustworthy & Interpretable AI
  • When Repository Labels Are Not Image-Level Truth: A Supervision Auditing Framework for Chest Radiograph AIYesika Alexandra Agudelo-Londoño
  • Evaluating Concept-guided Visual Counterfactual Generation in Medical ImagingSean Patrick Goggin
  • GPT-DBR: Decoding-Based Language-Model Regression for CT-Derived Lung-Function EstimationYoungSeok Kim
15:15 - 16:05 Coffee + Posters
16:05 - 16:40 KeynoteDr. Camila González, Medical University of Vienna, Austria
16:40 - 17:25 Oral Session 3: Label-Efficient & Weakly Supervised Segmentation
  • Fully Automated CT-Based Differential Diagnosis of Bowel Wall ThickeningZeineb Ben Chaaben
  • Label- and Parameter-Efficient Lung Ultrasound Representation Learning via I-JEPA for Edge DiagnosticsHeramb Vivek Patil
  • Annotation-Free Structured Delineation for Weakly Supervised PET Lesion SegmentationVicky De Ridder
  • LocSAM3: Box-Supervised Adaptation of SAM3 for Text-Only Chest X-Ray SegmentationAbdulrahman Mohamed Selim
17:25 - 17:50 Oral Session 4: Conference-to-Workshop Track
  • Quality-Guided Semi-Supervised Learning for Medical Image SegmentationKumar Abhishek
  • Group-Conditioned Representation Modulation for Fair Skin Disease DiagnosisGelei Xu
  • I²-Med: Interpretable Medical Inference through Visual-Guided Dynamic Logits CalibrationM. Sajid
  • Bayesian Temporal Pose Networks for Uncertainty-Calibrated Laparoscopic Tool Pose TrackingOmar Choudhry
17:50 - 18:00 Closing Remarks and Awards

Accepted Papers

# Title
4 Fully Automated CT-Based Differential Diagnosis of Bowel Wall Thickening
6 Multi-Caption Guided Weakly Supervised Disease Localization on Medical Cancer Images
7 When Repository Labels Are Not Image-Level Truth: A Supervision Auditing Framework for Chest Radiograph AI
9 FadeFormer: Content-Adaptive Graph Diffusion for Medical Image Classification
10 Replication and Reproducibility Analysis of Breast Tumor Classification and Segmentation Benchmarks on the BreastDM Dataset
13 Multi-Paradigm Fusion of XAI Methods for Chest X-ray Explanations
14 Label- and Parameter-Efficient Lung Ultrasound Representation Learning via I-JEPA for Edge Diagnostics
18 When Simple Wins: Lightweight CNN Encoders for Resource-Constrained Nucleus Segmentation
19 Feature Extraction Strategies for Clinically Significant Prostate Cancer Detection on Biparametric MRI: A Systematic Ablation of the Local-Global MIL Framework
20 Evaluating Concept-guided Visual Counterfactual Generation in Medical Imaging
21 KneeDINO: Cross-Plane Attention Fusion for Multi-Label Knee Pathology Detection with Grounded LLM Explainability
25 GraM-Diff: A Unified Graph–Mamba Diffusion Framework for EEG-Based Alzheimer's Disease Data Generation and Diagnosis
27 GPT-DBR: Decoding-Based Language-Model Regression for CT-Derived Lung-Function Estimation
28 Linear and Non-Linear Dimensionality Reduction for Hyperspectral Overlapping Chromosome Segmentation
31 Relational Learning of Temporal and Semantic Clinical Structured EHRs for Enhanced Patient Outcome Forecasting
36 Annotation-Free Structured Delineation for Weakly Supervised PET Lesion Segmentation
37 MedHyperGraph: EHR-Integrated Multimodal Hyperedges for Clinical VQA
38 LocSAM3: Box-Supervised Adaptation of SAM3 for Text-Only Chest X-Ray Segmentation
39 Label-Efficient Multimodal Microsleep Forecasting via Interpretable Disagreement-Driven Active Learning
40 GF-BrainSR: Gated Frequency-Aware Selective State Space Model-Based Brain MRI Image Super-resolution

Past Workshop Moments

Organization

Naren Akash

Naren Akash

President, MICCAI Student Board

IIIT Hyderabad, India

Cosmin I. Bercea

Cosmin I. Bercea

Vice-President, MICCAI Student Board

Technical University of Munich, Germany

Gelei Xu

Gelei Xu

Scientific Events Officer, MICCAI Student Board

University of Notre Dame, United States

MICCAI 2026 Young Scholars Initiative Committee

Camila González

Camila González

Assistant Professor

Medical University of Vienna, Austria

Numan Saeed

Numan Saeed

Research Scientist

MBZUAI, United Arab Emirates

Anees Kazi

Anees Kazi

Research Scientist

Harvard Medical School, United States

Baiying Lei

Baiying Lei

Distinguished Professor

Shenzhen University, China

Antonio Porras

Antonio Porras

Assistant Professor

University of Chicago, United States