Resources

7 results for "grounded radiology report generation"

Database Open Access

Radiology Report Generation Models Evaluation Dataset For Chest X-rays (RadEvalX)

Amos Rubin Calamida, Farhad Nooralahzadeh, Morteza Rohanian, et al.

The Radiology Report Generation Models Evaluation Dataset For Chest X-rays (RadEvalX) is publicly available and developed similarly to the ReXVal dataset. Just like ReXVal, RadEvalX focuses on radiologist evaluations of errors found in automatically…
Published: June 18, 2024. Version: 1.0.0
Database Restricted Access

CXRGraph: Using Information Extraction to Normalize the Training Data for Automatic Radiology Report Generation

Yuxiang Liao, Hoisang Heung, Hantao Liu, et al.

CXRGraph is a dataset of structured radiology reports dataset following the RadGraph format, which has been tailored for the Automatic Radiology Report Generation (ARRG) task. CXRGraph assorts clinical information from full-text radiology reports in…
relation extraction information extraction natural language processing structured radiology report named entity recognition
Published: Feb. 3, 2025. Version: 1.0.0
Database Credentialed Access

Radiology Report Expert Evaluation (ReXVal) Dataset

Feiyang Yu, Mark Endo, Rayan Krishnan, et al.

The Radiology Report Expert Evaluation (ReXVal) Dataset is a publicly available dataset of radiologist evaluations of errors in automatically generated radiology reports. The dataset contains annotations from 6 board certified radiologists on clinic…
Published: June 20, 2023. Version: 1.0.0
Database Credentialed Access

RaDialog Instruct Dataset

Chantal Pellegrini, Ege Özsoy, Benjamin Busam, et al.

Conversational AI tools that can generate and discuss clinically correct radiology reports for a given medical image have the potential to transform radiology. Such a human-in-the-loop radiology assistant could facilitate a collaborative diagnostic …
medical image understaning radiology chatbot radiology report generation radiology assistant large vision-language models
Published: July 12, 2024. Version: 1.1.0
Model Credentialed Access

RadVLM model

Nicolas Deperrois, Hidetoshi Matsuo, Samuel Ruiperez-Campillo, et al.

We present RadVLM, a compact (7B) multitask conversational foundation model designed for CXR interpretation. Its development relies on the curation of a large-scale instruction dataset comprising over 1 million image-instruction pairs containing bot…
Published: Oct. 8, 2025. Version: 1.0.0
Database Credentialed Access

RadVLM Instruction Dataset

Nicolas Deperrois, Hidetoshi Matsuo, Samuel Ruiperez-Campillo, et al.

We release the RadVLM instruction dataset, a large-scale resource used to train the RadVLM model on diverse radiology tasks. The dataset contains 1,115,021 image–instruction pairs spanning five task families: (i) report generation from frontal CXRs …
chest x-rays vision-language models medical ai
Published: Sept. 25, 2025. Version: 1.0.0
Database Restricted Access

LATTE-CXR: Locally Aligned TexT and imagE, Explainable dataset for Chest X-Rays

Elham Ghelichkhan, Tolga Tasdizen

Local annotation of medical data is both expensive and time-consuming due to the high cost of expert annotators, the precision required for accurate annotation, and the inherent challenges of medical diagnosis. To address these problems, we develop…
eye-tracking chest x-ray dataset automatically generated dataset caption-guided object detection image captioning with region-level description grounded radiology report generation phrase grounding xai multi-modal learning local visual-language models localization
Published: Feb. 4, 2025. Version: 1.0.0