Druh výsledku
článek ve sborníku
Popis
Intracranial hemorrhages (ICHs) are life-threatening brain injures with a relatively high incidence. In this
paper, the automatic algorithm for the detection and classification of ICHs, including localization, is
present. The set of binary convolutional neural network-based classifiers with an innovatively designed
cascade-parallel architecture is used. This automatic system may lead to a distinct decrease in the
diagnostic process’s duration in acute cases. An average Jaccard coefficient of 53.7% is achieved on the
data from the publicly available head CT dataset CQ500.
