Author

Ashwath Radhachandran

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#machine learning Preprint Sep 2026

UltraBench 2: Towards Robust Evaluation of Vision Foundation Models on Ultrasound

This work introduces UltraBench 2, a comprehensive benchmark with wide anatomical and task coverage, and a focus on standardization, reproducibility, and ease-of-use, and demonstrates that ultrasound-specific pretraining still leads on classification, but that state-of-the-art general-purpose models have drawn level on...

Ashwath Radhachandran, Adam Tupper, Christian Gagné et al. · 0 citations

#artificial intelligence Preprint Feb 2026

US-JEPA: A Joint Embedding Predictive Architecture for Ultrasound

This work proposes US-JEPA, a self-supervised framework that adopts the Static-teacher Asymmetric Latent Training (SALT) objective and demonstrates that masked latent prediction provides a stable and efficient path toward robust ultrasound representations.

Ashwath Radhachandran, Vedrana Ivezi'c, S. Athreya et al. · 0 citations