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From the 1 of 15 linked papers with an AI index.

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20242026
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cs.CV2026

TRACE-PCa: Predicting Prostate Cancer Progression from Longitudinal MRI During Active Surveillance

Hongye Zeng, Shreeram Athreya, Dingyuan Dai +4

The paper introduces an end-to-end model that leverages sequential MRI scans and clinical data to predict pathological progression in prostate cancer patients under active surveill…

cs.CV2026

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…

cs.CV2026

US-JEPA: A Joint Embedding Predictive Architecture for Medical Ultrasound

Ashwath Radhachandran, Vedrana Ivezić, Shreeram Athreya +3

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…

cs.CV2025

SPADE: Spatial Transcriptomics and Pathology Alignment Using a Mixture of Data Experts for an Expressive Latent Space

Ekaterina Redekop, Mara Pleasure, Zichen Wang +4

The rapid growth of digital pathology and advances in self-supervised deep learning have enabled the development of foundational models for various pathology tasks across diverse d…

cs.CV2025

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…