42 citations · 132 across the 10 of their papers we have counts for
10 papers
Unpaired Image-to-Image Translation via a Self-Supervised Semantic Bridge
Jiaming Liu, Felix Petersen, Yunhe Gao +6
Adversarial diffusion and diffusion-inversion methods have advanced unpaired image-to-image translation, but each faces key limitations. Adversarial approaches require target-domai…
Comp2Comp: Open-Source Software with FDA-Cleared Artificial Intelligence Algorithms for Computed Tomography Image Analysis
Adrit Rao, Malte Jensen, Andrea T. Fisher +28
Artificial intelligence allows automatic extraction of imaging biomarkers from already-acquired radiologic images. This paradigm of opportunistic imaging adds value to medical imag…
Explaining 3D Computed Tomography Classifiers with Counterfactuals
Joseph Paul Cohen, Louis Blankemeier, Akshay Chaudhari
Counterfactual explanations enhance the interpretability of deep learning models in medical imaging, yet adapting them to 3D CT scans poses challenges due to volumetric complexity…
Time-to-Event Pretraining for 3D Medical Imaging
Zepeng Huo, Jason Alan Fries, Alejandro Lozano +6
With the rise of medical foundation models and the growing availability of imaging data, scalable pretraining techniques offer a promising way to identify imaging biomarkers predic…
Automated detection of underdiagnosed medical conditions via opportunistic imaging
Asad Aali, Andrew Johnston, Louis Blankemeier +6
Abdominal computed tomography (CT) scans are frequently performed in clinical settings. Opportunistic CT involves repurposing routine CT images to extract diagnostic information an…
Merlin: A Computed Tomography Vision-Language Foundation Model and Dataset
Louis Blankemeier, Ashwin Kumar, Joseph Paul Cohen +37
The large volume of abdominal computed tomography (CT) scans coupled with the shortage of radiologists have intensified the need for automated medical image analysis tools. Previou…
GREEN: Generative Radiology Report Evaluation and Error Notation
Sophie Ostmeier, Justin Xu, Zhihong Chen +8
Evaluating radiology reports is a challenging problem as factual correctness is extremely important due to the need for accurate medical communication about medical images. Existin…
A dataset and benchmark for hospital course summarization with adapted large language models
Asad Aali, Dave Van Veen, Yamin Ishraq Arefeen +9
Brief hospital course (BHC) summaries are clinical documents that summarize a patient's hospital stay. While large language models (LLMs) depict remarkable capabilities in automati…
A Vision-Language Foundation Model to Enhance Efficiency of Chest X-ray Interpretation
Zhihong Chen, Maya Varma, Justin Xu +20
Over 1.4 billion chest X-rays (CXRs) are performed annually due to their cost-effectiveness as an initial diagnostic test. This scale of radiological studies provides a significant…
Identifying Spurious Correlations using Counterfactual Alignment
Joseph Paul Cohen, Louis Blankemeier, Akshay Chaudhari
Models driven by spurious correlations often yield poor generalization performance. We propose the counterfactual (CF) alignment method to detect and quantify spurious correlations…