Hybrid Intelligence in Medical Image Segmentation

Title of publication: Hybrid Intelligence in Medical Image Segmentation

The original dataset contains x-rays and corresponding masks. Some masks are missing so it is advised to cross-reference the images and masks. The dataset link consisting of train and test is attached here, 

https://www.kaggle.com/datasets/nikhilpandey360/chest-xray-masks-and-labels/data

The OP had the following request:It is requested that publications resulting from the use of this data attribute the source (National Library of Medicine, National Institutes of Health, Bethesda, MD, USA and Shenzhen No.3 People’s Hospital, Guangdong Medical College, Shenzhen, China) and cite the following publications:Jaeger S, Karargyris A, Candemir S, Folio L, Siegelman J, Callaghan F, Xue Z, Palaniappan K, Singh RK, Antani S, Thoma G, Wang YX, Lu PX, McDonald CJ. Automatic tuberculosis screening using chest radiographs. IEEE Trans Med Imaging. 2014 Feb;33(2):233-45. doi: 10.1109/TMI.2013.2284099. PMID: 24108713Candemir S, Jaeger S, Palaniappan K, Musco JP, Singh RK, Xue Z, Karargyris A, Antani S, Thoma G, McDonald CJ. Lung segmentation in chest radiographs using anatomical atlases with nonrigid registration. IEEE Trans Med Imaging. 2014 Feb;33(2):577-90. doi: 10.1109/TMI.2013.2290491. PMID: 24239990

The dataset is split into test and validation also so the final ones are attached as : train data, test data link and  

validation data link :The clinician masks are attached as: validation mask and testing mask.