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Intracranial hemorrhages (ICHs) are life-threatening brain injures with arelatively high incidence. In this paper, the automatic algorithm for thedetection and classification of ICHs, including localization, is present. Theset of binary convolutional neural network-based classifiers with a designedcascade-parallel architecture is used. This automatic system may lead to adistinct decrease in the diagnostic process's duration in acute cases. Anaverage Jaccard coefficient of 53.7 % is achieved on the data from the publiclyavailable head CT dataset CQ500.

Localization and classification of intracranialhemorrhages in CT data