COVID-19 Cell Detector

Here are our results in a COVID-19 challenge hosted by In this challenge the aim is to build a tool which is capable to diagnose COVID-19 (healthy or infected) from microscopic images of blood tests.


The challenge provides a set of training images with labels and a training set for prediction. Results of image prediction are submitted to the challenge host.

Images were provided by the Biological Research Centre (Peter Horvath), Szeged and by FIMM and University of Helsinki (Vilja Pietiäinen and Jussi Hepojoki). via

We are able to achieve high (+97%) precision, recall, auc, and acc predictions on hold-out images from the training set. On the training set we achieved 92.13% acc (only reported measure), tying for first place as of 8/15/2020.


Details on the data set are provided by the challenge host:

We are provided +433 images with labels (healthy or infected) for training and 217 images without labels for testing. The training set shows signs of curation, as despite various attempts the testing prediction results are 7-10% worse than hold-out testing sets of training images.




Contact authors for model




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