This is a dataset of 100 axial CT images.

Description 

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.

Data type

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

Publications

Post: https://medium.com/@hbjenssen/covid-19-radiology-data-collection-and-preparation-for-artificial-intelligence-4ecece97bb5b

Sites

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

Platform statistics

Subjects

 

 
Sessions

 

 
Modalities

 

 
110 110 110 CT + 110 segmentations (masks)
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