Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
368-02-004 ISMRM Abstract

Learning Diffeomorphic Augmentations via Variational Latent Modeling: A Study on 3D MRIs of the Knee Joint

Primary: Musculoskeletal - Cartilage
Secondary: Analysis Methods - Segmentation and Detection
368-02-004 · Segmentation for Musculoskeletal MRI Applications · Monday, 11 May, 9:15 AM–10:10 AM · Digital Posters Row I
Keywords: Segmentation Data Augmentation Variational Autoencoder Knee Joint Cartilage Deformation-based Morphometry
Accepted
Tonmoy Hossain1,2, Bruno Astuto 2, Ashok Vardhan Addala2, Fei Tan, Keerthi Sravan Ravi2, Miaomiao Zhang3, Ravi Soni2
1Computer Science, University of Virginia, Charlottesville, United States of America
2GE HealthCare, San Ramon, United States of America
3University of Virginia, Charlottesville, United States of America
Presenting Author: Bruno Astuto

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References

1. Hossain, Tonmoy, and Miaomiao Zhang. "Mgaug: Multimodal geometric augmentation in latent spaces of image deformations." Medical Image Analysis 102 (2025): 103540.
2. B. A. A. Nunes, I. Flament, N. Namiri, R. Shah, U. Bharadwaj, T. Link, M. Bucknor, V. Pedoia, S. Majumdar, “Automatic Deep Learning Assisted Detection and Grading of Abnormalities in Knee MRI Studies”, Radiology: AI, Jan 2021, doi: 10.1148/ryai.2021200165. [doi]
3. Hatamizadeh, Ali, et al. "Swin unetr: Swin transformers for semantic segmentation of brain tumors in mri images." International MICCAI brainlesion workshop. Cham: Springer International Publishing, 2021.

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/368-02-004