论文标题
CT数据中颅内诊断的定位和分类
Localization and classification of intracranialhemorrhages in CT data
论文作者
论文摘要
颅内出血（ICHS）是威胁生命的脑损伤，发病率相对较高。在本文中，存在用于检测和分类ICH（包括本地化）的自动算法。使用了具有设计的级联 - 平行体系结构的二进制卷积神经网络分类器集。在急性病例中，这种自动系统可能会导致诊断过程的持续时间明显减少。从公开可用的Head CT数据集CQ500的数据上，JACCARD系数为53.7％。
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 a 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.
