U-Net trained model for Lung dataset of Normal and Tuberculosis created by the National Library of Medicine in collaboration with the Department of Health and Human Services, Montgomery County, Maryland, USA.
Description
We trained a U-Net model on the dataset of lung annotations provided by expert Radiologist. For obtaining the dataset we quote the publication:
To use the trained model please download the U-Net model and vollseg-napari plugin from the napari hub to use the trained model on input images where the lungs are inside a 1024 by 1024 pixel size bounding box, for bigger lung images please downsample the image before applying the trained model.
1) Candemir S, Jaeger S, Musco J, Xue Z, Karargyris A, Antani SK, Thoma GR, Palaniappan K. 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
2) Jaeger S, Karargyris A, Candemir S, Folio L, Siegelman J, Callaghan FM, Xue Z, Palaniappan K,
Singh RK, Antani SK. Automatic tuberculosis screening using chest radiographs. IEEE Trans Med
Imaging. 2014 Feb;33(2):233-45. doi: 10.1109/TMI.2013.2284099. PMID: 24108713
