31 citations · 60 across the 9 of their papers we have counts for
9 papers
PETAR: Localized Findings Generation with Mask-Aware Vision-Language Modeling for PET Automated Reporting
Danyal Maqbool, Changhee Lee, Zachary Huemann +11
Generating automated reports for 3D positron emission tomography (PET) is an important and challenging task in medical imaging. PET plays a vital role in oncology, but automating r…
From Embeddings to Accuracy: Comparing Foundation Models for Radiographic Classification
Xue Li, Jameson Merkow, Noel C. F. Codella +11
Foundation models provide robust embeddings for diverse tasks, including medical imaging. We evaluate embeddings from seven general and medical-specific foundation models (e.g., De…
Scalable Drift Monitoring in Medical Imaging AI
Jameson Merkow, Felix J. Dorfner, Xiyu Yang +6
The integration of artificial intelligence (AI) into medical imaging has advanced clinical diagnostics but poses challenges in managing model drift and ensuring long-term reliabili…
Is Open-Source There Yet? A Comparative Study on Commercial and Open-Source LLMs in Their Ability to Label Chest X-Ray Reports
Felix J. Dorfner, Liv Jürgensen, Leonhard Donle +11
Introduction: With the rapid advances in large language models (LLMs), there have been numerous new open source as well as commercial models. While recent publications have explore…
3D-MIR: A Benchmark and Empirical Study on 3D Medical Image Retrieval in Radiology
Asma Ben Abacha, Alberto Santamaria-Pang, Ho Hin Lee +9
The increasing use of medical imaging in healthcare settings presents a significant challenge due to the increasing workload for radiologists, yet it also offers opportunity for en…
Region-based Contrastive Pretraining for Medical Image Retrieval with Anatomic Query
Ho Hin Lee, Alberto Santamaria-Pang, Jameson Merkow +4
We introduce a novel Region-based contrastive pretraining for Medical Image Retrieval (RegionMIR) that demonstrates the feasibility of medical image retrieval with similar anatomic…
CheXstray: Real-time Multi-Modal Data Concordance for Drift Detection in Medical Imaging AI
Arjun Soin, Jameson Merkow, Jin Long +6
Clinical Artificial lntelligence (AI) applications are rapidly expanding worldwide, and have the potential to impact to all areas of medical practice. Medical imaging applications…
DeepRadiologyNet: Radiologist Level Pathology Detection in CT Head Images
Jameson Merkow, Robert Lufkin, Kim Nguyen +3
We describe a system to automatically filter clinically significant findings from computerized tomography (CT) head scans, operating at performance levels exceeding that of practic…
Dense Volume-to-Volume Vascular Boundary Detection
Jameson Merkow, David Kriegman, Alison Marsden +1
In this work, we present a novel 3D-Convolutional Neural Network (CNN) architecture called I2I-3D that predicts boundary location in volumetric data. Our fine-to-fine, deeply super…