MedSeg Covid Dataset 1

This is a dataset of 100 axial CT images from &gt;40 patients with COVID-19 that were converted from openly accessible JPG images found at https://www.sirm.org/en/ . The conversion process is described in detail in the following blogpost: https://medium.com/@hbjenssen/covid-19-radiology-data-collection-and-preparation-for-artificial-intelligence-4ecece97bb5b<br>In short, the images were segmented by a radiologist using 3 labels: <em>ground-glass</em> (mask value =1), <em>consolidation</em> (=2) and <em>pleural effusion</em> (=3). We then trained a 2d multilabel U-Net model, which you can find and apply in MedSeg