Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition - Analysis Theory in MRI: Learning and Evaluation Concepts

Analysis Theory in MRI: Learning and Evaluation Concepts

Weekend Course

Image Acquisition & Analysis

Saturday, 09 May 2026

Ballroom East

13:00 - 17:00

Moderators: Carlos Castillo-Passi & Chiara Coletti

Session Number: 104-02

No CME/CE Credit

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This session introduces foundational concepts in MRI analysis using classical, machine learning, and deep learning techniques. Topics include classification, segmentation, quantification, registration, and evaluation metrics. The goal is to provide attendees with a theoretical understanding to support practical MRI analysis.

Skill Level: Basic,Intermediate

13:00		104-02-001. The Evolving Role of Image Analysis in Clinical MRI Workflows Thomas Küstner University Hospital Tuebingen, Tuebingen, Germany
13:30		104-02-002. AI for Clinical Diagnosis: Classification Models Using Machine Learning and Deep Learning Cem Deniz NYU Langone Health, New York, United States of America
14:00		104-02-003. Segmentation in MRI: Challenges and Solutions Julien Cohen-Adad Polytechnique Montreal, Montreal, Canada, Canada
14:30 - 15:00 — Break & Meet the Teachers
15:00		104-02-004. Quantification and Modeling in MRI: Concepts and Applications Ekin Karasan UC Berkeley, Berkeley, United States of America
15:30		104-02-005. Registration in MRI: Concepts, Challenges, and Modern Approaches Kanghyun Ryu Korea Institute of Science and Technology (KIST), Seould, Korea, Republic of
16:00		104-02-006. Evaluation Metrics and Loss Functions for MRI Analysis Tasks Veronika Spieker Helmholtz Munich, Munich, Germany
16:30		104-02-007. Panel Discussion Cem Deniz NYU Langone Health, New York, United States of America Julien Cohen-Adad Polytechnique Montreal, Montreal, Canada, Canada Ekin Karasan UC Berkeley, Berkeley, United States of America Kanghyun Ryu Korea Institute of Science and Technology (KIST), Seould, Korea, Republic of Veronika Spieker Helmholtz Munich, Munich, Germany