173 citations · 319 across the 8 of their papers we have counts for
9 papers
ViLLA: Fine-Grained Vision-Language Representation Learning from Real-World Data
Maya Varma, Jean-Benoit Delbrouck, Sarah Hooper +2
Vision-language models (VLMs), such as CLIP and ALIGN, are generally trained on datasets consisting of image-caption pairs obtained from the web. However, real-world multimodal dat…
The Effect of Counterfactuals on Reading Chest X-rays
Joseph Paul Cohen, Rupert Brooks, Sovann En +4
This study evaluates the effect of counterfactual explanations on the interpretation of chest X-rays. We conduct a reader study with two radiologists assessing 240 chest X-ray pred…
Exploring Image Augmentations for Siamese Representation Learning with Chest X-Rays
Rogier van der Sluijs, Nandita Bhaskhar, Daniel Rubin +2
Image augmentations are quintessential for effective visual representation learning across self-supervised learning techniques. While augmentation strategies for natural imaging ha…
RoentGen: Vision-Language Foundation Model for Chest X-ray Generation
Pierre Chambon, Christian Bluethgen, Jean-Benoit Delbrouck +7
Multimodal models trained on large natural image-text pair datasets have exhibited astounding abilities in generating high-quality images. Medical imaging data is fundamentally dif…
Adapting Pretrained Vision-Language Foundational Models to Medical Imaging Domains
Pierre Chambon, Christian Bluethgen, Curtis P. Langlotz +1
Multi-modal foundation models are typically trained on millions of pairs of natural images and text captions, frequently obtained through web-crawling approaches. Although such mod…
TorchXRayVision: A library of chest X-ray datasets and models
Joseph Paul Cohen, Joseph D. Viviano, Paul Bertin +8
TorchXRayVision is an open source software library for working with chest X-ray datasets and deep learning models. It provides a common interface and common pre-processing chain fo…
Designing Counterfactual Generators using Deep Model Inversion
Jayaraman J. Thiagarajan, Vivek Narayanaswamy, Deepta Rajan +3
Explanation techniques that synthesize small, interpretable changes to a given image while producing desired changes in the model prediction have become popular for introspecting b…
MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation
Alexandros Karargyris, Renato Umeton, Micah J. Sheller +39
Medical AI has tremendous potential to advance healthcare by supporting the evidence-based practice of medicine, personalizing patient treatment, reducing costs, and improving prov…
MRSaiFE: Tissue Heating Prediction for MRI: a Feasibility Study
Simone Angela Winkler, Isabelle Saniour, Akshay Chaudhari +2
A to-date unsolved and highly limiting safety concern for Ultra High-Field (UHF) magnetic resonance imaging (MRI) is the deposition of radiofrequency (RF) power in the body, quanti…