Resources

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…

MIMIC-CXR-DB is a relational clinical database comprising 146,333 chest radiographs linked to hospital admissions, designed to support research at the intersection of electronic health records (EHRs) and chest radiography. The database integrates ho…

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…

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…

MIMIC-CXR is a large, open source dataset that is widely-used in medical AI research. One of the limitations of this dataset is the lack of ground truth labels for the chest X-ray studies. Prior work has extracted structured labels from the MIMIC-CX…

The MUSIC (MUerte Subita en Insuficiencia Cardiaca) study is a prospective, multicentre, longitudinal study designed to assess risk predictors of cardiac mortality and sudden cardiac death (SCD) in ambulatory patients with chronic heart failure (CHF…

Automatic medical report generation (MRG) towards describing life-threatening lesions from given medical images, such as Chest X-ray and Fundus Fluorescein Angiography (FFA), has been a long-standing research topic in machine learning and automatic …

We release a new dataset, MS-CXR, with locally-aligned phrase grounding annotations by board-certified radiologists to facilitate the study of complex semantic modelling in biomedical vision–language processing. The MS-CXR dataset provides 1162 imag…

COVID Data for Shared Learning (CDSL) is a multimodal database comprising de-identified medical data from 4,479 patients who were hospitalized with confirmed or suspected COVID-19 in the Spanish 'HM Hospitales' group from 2019-12-26 to 2021-02-13. T…

Generative vision-language models have exciting potential implications for radiology report generation, but unfortunately such models are also known to produce hallucinations and other nonsensical statements. For example, radiology report generation…