This is a dataset of 100 axial CT images.
This is a dataset of 100 axial CT images from the Italian Society of Medical and Interventional Radiology’s excellent collection of about 60 patients with Covid-19 that were converted from openly accessible JPG images.
The database contains 60 cases with example CXRs and single slice CT-images. A simple download from these cases resulted in 110 usable, axial CT-images of confirmed COVID-19 cases.
The images were segmented by a radiologist using 3 labels: ground-glass (mask value =1), consolidation (=2) and pleural effusion (=3). Then they trained a 2d multilabel U-Net model, which you can find and apply in MedSeg. 10 images were left out for validation/testing.
The conversion process is described in detail in the following post: Covid-19 radiology — data collection and preparation for Artificial Intelligence
Italian Society of Medical and Interventional Radiology’s (https://www.sirm.org/category/senza-categoria/covid-19/)
Dataset size estimation
|Dataset||Total size aprox.||Session size aprox.|
|CT segmentation dataset||167,4 MB||1,5 MB|
|110||110||110 CT + 110 segmentations (masks)|