  The outbreak of the SARS-CoV-2 pandemic has put healthcare systems worldwide
to their limits, resulting in increased waiting time for diagnosis and required
medical assistance. With chest radiographs (CXR) being one of the most common
COVID-19 diagnosis methods, many artificial intelligence tools for image-based
COVID-19 detection have been developed, often trained on a small number of
images from COVID-19-positive patients. Thus, the need for high-quality and
well-annotated CXR image databases increased. This paper introduces POLCOVID
dataset, containing chest X-ray (CXR) images of patients with COVID-19 or
other-type pneumonia, and healthy individuals gathered from 15 Polish
hospitals. The original radiographs are accompanied by the preprocessed images
limited to the lung area and the corresponding lung masks obtained with the
segmentation model. Moreover, the manually created lung masks are provided for
a part of POLCOVID dataset and the other four publicly available CXR image
collections. POLCOVID dataset can help in pneumonia or COVID-19 diagnosis,
while the set of matched images and lung masks may serve for the development of
lung segmentation solutions.
