Resources

The task of Difference Visual Question Answering involves answering questions about the difference between a pair of main and reference images. This process is consistent with the radiologist's diagnosis practice that compares the current image with…

Medical Visual Question Answering (VQA) is an important task in medical multi-modal Large Language Models (LLMs), aiming to answer clinically relevant questions regarding input medical images. This technique has the potential to improve the efficien…

MIMIC CXR [1] is a large publicly available dataset of chest radiographs in DICOM format with free-text radiology reports. In addition, labels for the presence of 12 different chest-related pathologies, as well as of any support devices, and overall…

Segmenting the heart and lungs from chest X-ray images is essential for accurate disease diagnosis, enabling the calculation of image-derived digital biomarkers for cardiopulmonary health assessment. Furthermore, creation of annotated data sets can …

Clinical management decisions for patients with acutely decompensated heart failure and many other diseases are often based on grades of pulmonary edema severity, rather than its mere absence or presence. Chest radiographs are commonly performed to …

Radiology reports are essential for clinical care but pose challenges for automated processing due to their unstructured nature. Existing datasets like RadGraph-1.0 focus narrowly on chest X-rays (CXR), limiting their applicability. We introduce Rad…

The MIMIC Chest X-ray (MIMIC-CXR) Database v2.0.0 is a large publicly available dataset of chest radiographs in DICOM format with free-text radiology reports. The dataset contains 377,110 images corresponding to 227,835 radiographic studies performe…

MS-CXR-T is a multi-modal benchmark dataset for evaluating biomedical vision-language processing (VLP) models on two distinct temporal tasks in radiology: image classification and sentence similarity. The former comprises multi-image frontal chest X…

A multimodal combination of the MIMIC-IV v1.0.0 and MIMIC Chest X-ray (MIMIC-CXR-JPG) v2.0.0 databases filtered to only include patients that have at least one chest X-ray performed with the goal of validating multi-modal predictive analytics in hea…

CXR-Align is a benchmark dataset designed to evaluate vision-language processing (VLP) models' ability to accurately interpret negations in chest X-ray (CXR) reports. Negations are prevalent in medical documentation and pose significant challenges f…