# Localization and classification of intracranialhemorrhages in CT data

arXiv: https://arxiv.org/abs/2009.03046 · HTML: https://mlsanity.com/paper/2009.03046/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Sep 2020.

## Built on by (most cited first, 1 of 1)

- [Weakly supervised deep learning-based intracranial hemorrhage localization](https://mlsanity.com/paper/2105.00781/) (2021)

## Abstract (arXiv)

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.