Detail publikace

Detection of intracranial haemorrhages in head CT data based on deep learning

NEMČEK, J.

Originální název

Detection of intracranial haemorrhages in head CT data based on deep learning

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

In this paper, we present a method for detection of intracranial haemorrhages in the head CT data using convolutional neural networks. We introduce three 2D image classifiers that perform in three perpendicular anatomical planes and classify the CT slices into healthy or pathological, whereby they provide the information about the position of the haemorrhage in the 3D CT im-age. The accuracies of the three models are 90.19%, 88.15%, and 80.90% for the axial, sagital and coronal plane.

Klíčová slova

Intracranial haemorrhage, CT, classification, detection, convolutional neural network

Autoři

NEMČEK, J.

Vydáno

23. 4. 2020

Nakladatel

Brno University of Technolog, Faculty of Electrical Engineering anf Communication

Místo

Brno

ISBN

978-80-214-5868-0

Kniha

Proceedings II of the 26th Conference STUDENT EEICT 2020

Strany od

72

Strany do

75

Strany počet

4

URL

https://www.fekt.vut.cz/conf/EEICT/archiv/sborniky/EEICT_2020_sbornik_2.pdf

BibTex

@inproceedings{BUT164865,
  author="Jakub {Nemček}",
  title="Detection of intracranial haemorrhages in head CT data based on deep learning",
  booktitle="Proceedings II of the 26th Conference STUDENT EEICT 2020",
  year="2020",
  pages="72--75",
  publisher="Brno University of Technolog, Faculty of Electrical Engineering anf Communication",
  address="Brno",
  isbn="978-80-214-5868-0",
  url="https://www.fekt.vut.cz/conf/EEICT/archiv/sborniky/EEICT_2020_sbornik_2.pdf"
}