activity
20182025
most citedSynthetically Enhanced: Unveiling Synthetic Data's Potential in Medical Imaging Research

58 citations · 125 across the 24 of their papers we have counts for

collaborators
Showing cs.CVShow all

10 papers · 1 filter

cs.CV2025★ 1 cited

Mammo-FM: Breast-specific foundational model for Integrated Mammographic Diagnosis, Prognosis, and Reporting

Shantanu Ghosh, Vedant Parthesh Joshi, Rayan Syed +14

Breast cancer is one of the leading causes of death among women worldwide. We introduce Mammo-FM, the first foundation model specifically for mammography, pretrained on the largest…

cs.CV2025

Feature Quality and Adaptability of Medical Foundation Models: A Comparative Evaluation for Radiographic Classification and Segmentation

Frank Li, Theo Dapamede, Mohammadreza Chavoshi +12

Foundation models (FMs) promise to generalize medical imaging, but their effectiveness varies. It remains unclear how pre-training domain (medical vs. general), paradigm (e.g., tex…

cs.CV2025

Evaluating Vision Language Models (VLMs) for Radiology: A Comprehensive Analysis

Frank Li, Hari Trivedi, Bardia Khosravi +8

Foundation models, trained on vast amounts of data using self-supervised techniques, have emerged as a promising frontier for advancing artificial intelligence (AI) applications in…

cs.CV2024

Emory Knee Radiograph (MRKR) Dataset

Brandon Price, Jason Adleberg, Kaesha Thomas +6

The Emory Knee Radiograph (MRKR) dataset is a large, demographically diverse collection of 503,261 knee radiographs from 83,011 patients, 40% of which are African American. This da…

cs.CV2023

Hierarchical Classification System for Breast Cancer Specimen Report (HCSBC) -- an end-to-end model for characterizing severity and diagnosis

Thiago Santos, Harish Kamath, Christopher R. McAdams +8

Automated classification of cancer pathology reports can extract information from unstructured reports and categorize each report into structured diagnosis and severity categories.…

cs.CV2023★ 2 cited

Benchmarking bias: Expanding clinical AI model card to incorporate bias reporting of social and non-social factors

Carolina A. M. Heming, Mohamed Abdalla, Shahram Mohanna +8

Clinical AI model reporting cards should be expanded to incorporate a broad bias reporting of both social and non-social factors. Non-social factors consider the role of other fact…