1 citations · 1 across the 5 of their papers we have counts for
7 papers
TRACE-PCa: Predicting Prostate Cancer Progression from Longitudinal MRI During Active Surveillance
Hongye Zeng, Shreeram Athreya, Dingyuan Dai +4
Active surveillance (AS) is the preferred strategy for favorable-risk prostate cancer, yet current protocols rely on scheduled repeat biopsies, most of which reveal no progression…
Pretext Matters: An Empirical Study of SSL Methods in Medical Imaging
Vedrana Ivezić, Mara Pleasure, Ashwath Radhachandran +7
Though self-supervised learning (SSL) has demonstrated incredible ability to learn robust representations from unlabeled data, the choice of optimal SSL strategy can lead to vastly…
US-JEPA: A Joint Embedding Predictive Architecture for Ultrasound
Ashwath Radhachandran, Vedrana Ivezić, Shreeram Athreya +2
Ultrasound (US) imaging poses unique challenges for representation learning due to its inherently noisy acquisition process. The low signal-to-noise ratio and stochastic speckle pa…
DSA-NRP: No-Reflow Prediction from Angiographic Perfusion Dynamics in Stroke EVT
Shreeram Athreya, Carlos Olivares, Ameera Ismail +3
Following successful large-vessel recanalization via endovascular thrombectomy (EVT) for acute ischemic stroke (AIS), some patients experience a complication known as no-reflow, de…
CytoFM: The first cytology foundation model
Vedrana Ivezić, Ashwath Radhachandran, Ekaterina Redekop +5
Cytology is essential for cancer diagnostics and screening due to its minimally invasive nature. However, the development of robust deep learning models for digital cytology is cha…
Reducing Overtreatment of Indeterminate Thyroid Nodules Using a Multimodal Deep Learning Model
Shreeram Athreya, Andrew Melehy, Sujit Silas Armstrong Suthahar +9
Objective: Molecular testing (MT) classifies cytologically indeterminate thyroid nodules as benign or malignant with high sensitivity but low positive predictive value (PPV), only…