Schedule and accepted papers for the MICCAI 2026 Doctoral Symposium
All accepted participants present a poster.
Accepted for the PhD Thesis Madness competition (1-16). Oral presentations on September 29, 2026, 12:30 PM - 1:30 PM, 2 minutes each. All Madness participants also present a poster. Organizing committee members are not eligible for awards, even if they receive a Madness slot.
| # | Title | Author |
|---|---|---|
| 1 | Structured Priors for Ill-Posed Surgical and Medical Scene Understanding | Hritam Basak |
| 2 | Toward Clinically Robust Continual Learning: Efficiency, Generalization, Fairness, and Beyond | Nourhan Bayasi |
| 3 | From Geometry to Bone Union: Bridging Physics-Based Optimization and Generative AI in Mandibular Reconstruction Surgery | Hamidreza Aftabi |
| 4 | Supervised and Self-Supervised Learning for 3D Medical Foundation Models | Constantin Ulrich |
| 5 | Advancing Deep Learning Across the Medical Imaging Pipeline: From Disease Phenotyping to Treatment Optimization | Isabella Poles |
| 6 | Subgroup-Robust Medical AI for Reliable Diagnosis Across Heterogeneous Patient Populations | Gelei Xu |
| 7 | Deep Geometric Medical Image Analysis Grounded in Topologically Consistent Surfaces | Fabian Bongratz |
| 8 | Multimodal Intelligence for Endoscopic Surgery: From Perception Restoration to Interactive Execution | Long Bai |
| 9 | Quality Comes First: Automated Auditing of Upper Gastrointestinal Endoscopy | Diego Bravo |
| 10 | Rethinking Data, Annotation, and Targets in Deep Learning for Skin Image Analysis | Kumar Abhishek |
| 11 | Artificial Intelligence for Hematological Diagnostics: From Single-Cell Analysis to Disease Classification | Ario Sadafi |
| 12 | Learning to Unify Complex Geometric Shape With Image Texture Representations For Healthcare Applications | Tonmoy Hossain |
| 13 | Clinical User-Centered Explainable AI for Medical Image Analysis | Weina Jin |
| 14 | Clinically Aligned Deep Learning for Medical Image Interpretation | Gregory Holste |
| 15 | Hardware-Efficient, Scalable, and Label-Efficient Deep Learning Methods for Medical Imaging | Md Mostafijur Rahman |
| 16 | Controllable Diffusion Models for Data Scarcity in Computational Pathology | Hyun-Jic Oh |
Spotlight posters (17-29).
| # | Title | Author |
|---|---|---|
| 17 | Focal CSVD Biomarkers for Heart-Brain and Cognitive Studies | Lucas He |
| 18 | Geometric Priors for Generalizable Deep Learning in Medical Image Segmentation and Generation | Tomasz Szczepański |
| 19 | 3D Brain Shape Modeling for Neuroanatomical Analysis and Longitudinal Prediction | Wonjung Park |
| 20 | From Explanation Stability to Wavelet-Domain Generation: Trustworthy Brain Age Modeling from Structural MRI | Danilo Danese |
| 21 | Advancing White Matter Tract Analysis Through Interactive Machine Learning: Methods and Applications | Robin Peretzke |
| 22 | Virtual Tagging: Geometry-based Navigation to Marked Locations in Colonoscopy | Samuel Ehrenstein |
| 23 | Lessons from autoPET: Benchmarking, Failure Analysis and Clinical Validity of Automated Lesion Segmentation in Whole-Body PET/CT | Jakob Dexl |
| 24 | Reliable and Explainable Learning for Radiographic Catheter Assessment | Yuhan Wang |
| 25 | Learning from Incomplete Multimodal Evidence | Seunghun Baek |
| 26 | Anatomically-informed deep learning for intracranial aneurysm detection | Alberto Mario Ceballos Arroyo |
| 27 | Advancing Myocardial Function Imaging in Echocardiography using Point Tracking | Md Abulkalam Azad |
| 28 | Effective Medical Image Segmentation under Joint Compute and Annotation Budgets | Juntao Jiang |
| 29 | Retrieval-Grounded Vision-Language Modeling for Medical Diagnosis | Mai A. Shaaban |
Regular posters (30-47).
| # | Title | Author |
|---|---|---|
| 30 | Structure-Aware Deep Learning for Surgical Video Understanding: From Segmentation to Constraint-Aware Anticipation | Md Rezowan Ferdous Shuvo |
| 31 | Towards Robust and Fair AI-enabled Echocardiography Image Segmentation | Iman Islam |
| 32 | Towards End-to-End Privacy-Preserving AI for Real-Time ECG Monitoring | Beyazıt Bestami YÜKSEL |
| 33 | AI-Based Analysis of Longitudinal Cardiac MRI | Dewmini Hasara Wickremasinghe |
| 34 | Vision Transformer-Based Generative AI for Multilingual Medical Image Captioning and Speech Synthesis to Support Visually Impaired Patients | Dawit Shibabaw |
| 35 | Knowledge-Focused Language Modelling and Modular Component Reuse in Medical Vision-Language Models | Yunsoo Kim |
| 36 | Region of Physicians' Interest to Identify Clinically Important Finding in High-Volume Imaging Data | Naoki Okada |
| 37 | Learning Representations of Pathology Images for Enhanced Compression and Virtual Staining | Maximilian Fischer |
| 38 | Radiology-Pathology Fusion for Neoadjuvant Therapy Response Prediction in Breast Cancer | Song Zhang |
| 39 | Deep Learning for Automated Reporting in Breast Magnetic Resonance Imaging | Kai Geissler |
| 40 | Beyond the single scan: neuroimaging-inspired standardization and population references in lung cancer screening | Giulia Raffaella De Luca |
| 41 | Deep Learning-Based TMJ Ultrasound Segmentation for Clinical Joint-Space Assessment: Toward Generalizable, Clinically Deployable AI | Shradhdha Trivedi |
| 42 | Structured Conditioning for Controllable Medical Image Synthesis | Zolnamar Dorjsembe |
| 43 | Information-Theoretic Evaluation and Model-Specific Interpretation of Medical Imaging AI | Sourya Sengupta |
| 44 | An End-to-End Deep Learning Framework for Automated Scoliosis Assessment in Ultrasound Imaging | Chen Zhang |
| 45 | Anatomy of Unequal Errors: Data Gaps, Encoded Signals, and Group-Specific Decisions | Vien Ngoc Dang |
| 46 | Development and Evaluation of a Representation-Aware Computational Pathology Pipeline for Histopathological Whole Slide Image Analysis | Richa Malviya dutta |
| 47 | Facial Imaging Based Deep Learning for Cardio-metabolic Risk Prediction and Automated Severity Grading in Chronic Plaque Psoriasis | Lavina Rajput |
Posters: All accepted participants, including PhD Thesis Madness invitees, present a poster on Monday, September 28, 2026, from 16:00 to 18:00 (local time). Evaluation takes place at the poster session.
PhD Thesis Madness: Oral presentations take place on September 29, 2026, from 12:30 PM to 1:30 PM (Day 2 of the main conference). Each presentation is 2 minutes. Organizing committee members are not eligible for awards, even if they receive a PhD Thesis Madness slot.