Detection of intracranial haemorrhages in head CT data based on deep learning
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F20%3APU137079" target="_blank" >RIV/00216305:26220/20:PU137079 - isvavai.cz</a>
Result on the web
<a href="https://www.fekt.vut.cz/conf/EEICT/archiv/sborniky/EEICT_2020_sbornik_2.pdf" target="_blank" >https://www.fekt.vut.cz/conf/EEICT/archiv/sborniky/EEICT_2020_sbornik_2.pdf</a>
DOI - Digital Object Identifier
—
Alternative languages
Result language
angličtina
Original language name
Detection of intracranial haemorrhages in head CT data based on deep learning
Original language description
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.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
20601 - Medical engineering
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings II of the 26th Conference STUDENT EEICT 2020
ISBN
978-80-214-5868-0
ISSN
—
e-ISSN
—
Number of pages
4
Pages from-to
72-75
Publisher name
Brno University of Technolog, Faculty of Electrical Engineering anf Communication
Place of publication
Brno
Event location
BRNO
Event date
Apr 23, 2020
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
000598376500019