7 papers
Closing the Performance Gap Between AI and Radiologists in Chest X-Ray Reporting
Harshita Sharma, Maxwell C. Reynolds, Valentina Salvatelli +26
AI-assisted report generation offers the opportunity to reduce radiologists' workload stemming from expanded screening guidelines, complex cases and workforce shortages, while main…
NOVA: An Agentic Framework for Automated Histopathology Analysis and Discovery
Anurag J. Vaidya, Felix Meissen, Daniel C. Castro +7
Digitized histopathology analysis involves complex, time-intensive workflows and specialized expertise, limiting its accessibility. We introduce NOVA, an agentic framework that tra…
PadChest-GR: A Bilingual Chest X-ray Dataset for Grounded Radiology Report Generation
Daniel C. Castro, Aurelia Bustos, Shruthi Bannur +11
Radiology report generation (RRG) aims to create free-text radiology reports from clinical imaging. Grounded radiology report generation (GRRG) extends RRG by including the localis…
Insights into a radiology-specialised multimodal large language model with sparse autoencoders
Kenza Bouzid, Shruthi Bannur, Felix Meissen +4
Interpretability can improve the safety, transparency and trust of AI models, which is especially important in healthcare applications where decisions often carry significant conse…
Exploring scalable medical image encoders beyond text supervision
Fernando Pérez-GarcÃa, Harshita Sharma, Sam Bond-Taylor +12
Language-supervised pre-training has proven to be a valuable method for extracting semantically meaningful features from images, serving as a foundational element in multimodal sys…
MAIRA-Seg: Enhancing Radiology Report Generation with Segmentation-Aware Multimodal Large Language Models
Harshita Sharma, Valentina Salvatelli, Shaury Srivastav +13
There is growing interest in applying AI to radiology report generation, particularly for chest X-rays (CXRs). This paper investigates whether incorporating pixel-level information…