COVID-CT-Rate.zip

COVID-CT-Rate is a dataset including 433 CT images from 82 COVID-19 patients with their associated infection masks. It can be used for training AI models to segment COVID-19 lesions from chest CT images.For the annotation process, first, infection masks were generated using a standard U-Net pre-trained on a public COVID-19 dataset. Then, a thoracic radiologist with 20 years of experience in lung imaging carefully modified and verified the generated infection masks. All CT images have been obtained without contrast enhancement and saved in the Digital Imaging and Communications in Medicine (DICOM) format and the Hounsfield Unit.CT images have been selected from diffident parts of the lung (top, middle, and bottom) with different infection rates to help the AI model better predict the infection regions on unseen CT images from the whole lung volume.DICOM files for each patient have been saved in individual folders within the COVID-Rate-CT directory, and corresponding infection masks, labeled with patient and image numbers, have been stored in the COVID-Rate-Masks directory.For ease of use, you can also download CT images and infection masks from the <code>CTs.npy and </code>InfMasks<code>.npy</code> files. <br>If you found this dataset helpful to your research, please consider citing:<br>Enshaei N, Oikonomou A, Rafiee MJ, Afshar P, Heidarian S, Mohammadi A, Plataniotis KN, Naderkhani F. COVID-rate: an automated framework for segmentation of COVID-19 lesions from chest CT images. Scientific Reports. 2022 Feb 25;12(1):3212.