most citedA self-supervised framework for learning whole slide representations

3 citations · 4 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Health system learning achieves generalist neuroimaging models

Akhil Kondepudi, Akshay Rao, Chenhui Zhao +14

Frontier artificial intelligence (AI) models, such as OpenAI's GPT-5 and Meta's DINOv3, have advanced rapidly through training on internet-scale public data, yet such systems lack…

cs.CV2025

Learning neuroimaging models from health system-scale data

Yiwei Lyu, Samir Harake, Asadur Chowdury +18

Neuroimaging is a ubiquitous tool for evaluating patients with neurological diseases. The global demand for magnetic resonance imaging (MRI) studies has risen steadily, placing sig…

eess.IV2024

Super-resolution of biomedical volumes with 2D supervision

Cheng Jiang, Alexander Gedeon, Yiwei Lyu +7

Volumetric biomedical microscopy has the potential to increase the diagnostic information extracted from clinical tissue specimens and improve the diagnostic accuracy of both human…

eess.IV2024★ 1 cited

Step-Calibrated Diffusion for Biomedical Optical Image Restoration

Yiwei Lyu, Sung Jik Cha, Cheng Jiang +7

High-quality, high-resolution medical imaging is essential for clinical care. Raman-based biomedical optical imaging uses non-ionizing infrared radiation to evaluate human tissues…

cs.CV2024★ 3 cited

A self-supervised framework for learning whole slide representations

Xinhai Hou, Cheng Jiang, Akhil Kondepudi +4

Whole slide imaging is fundamental to biomedical microscopy and computational pathology. Previously, learning representations for gigapixel-sized whole slide images (WSIs) has reli…