MedSeg Covid Dataset 1
Version 2 2021-01-05, 08:15Version 2 2021-01-05, 08:15
Version 1 2021-01-05, 08:05Version 1 2021-01-05, 08:05
dataset
posted on 2021-01-05, 08:15 authored by MedSegMedSeg, Håvard Bjørke Jenssen, Tomas SakinisThis is a dataset of 100 axial CT images from >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: Covid-19 radiology — data collection and preparation for Artificial Intelligence
In short, the images were segmented by a radiologist using 3 labels: ground-glass (mask value =1), consolidation (=2) and pleural effusion (=3). We then trained a 2d multilabel U-Net model, which you can find and apply in MedSeg
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