401-02-009 ISMRM Abstract

A Foundation Model-Driven Framework for Automated QA of Medical Imaging AI Solutions

Primary: Analysis Methods - Foundation Models

Secondary: Analysis Methods - Visualization

401-02-009 · Foundation Models · Tuesday, 12 May, 8:20 AM–10:10 AM · Hall 1A

Keywords: Foundation model Deep Learning Segmentation Vision Transformer model Deep learning classification Artificial Intelligence in MRI

Accepted

Jayesh Tripathi ¹, Gurunath Reddy Madhumani¹, Sajith Rajamani¹, Vanika Singhal¹, Bhavatharani Sundararajan¹, Garvita K Basantani¹, Sneha Sree C¹, Alvin Ronnie¹, Tisha A Abraham¹, Chitresh Bhushan², Dattesh Dayanand Shanbhag¹

¹GE HealthCare, Bengaluru, India

²GE HealthCare, San Ramon, United States of America

Presenting Author: Jayesh Tripathi

Synopsis

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References

1. Shanbhag DD, Bhushan C, Maximo A, et al. A generalized deep learning framework for multi-landmark intelligent slice placement using standard tri-planar 2D localizers. ISMRM 2019 ; p.670

2. Liu, Yang and Zhu, Muzhi and Li, Hengtao et al. Matcher: Segment Anything with One Shot Using All-Purpose Feature Matching. ICLR 2024

3. Maxime Oquab, Timothée Darcet, Théo Moutakanni, et al. DINOv2: Learning Robust Visual Features without Supervision. TMLR 2024

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/401-02-009