Classification of cross-sections for vascular skeleton extraction using convolutional neural networks
author
Lidayová, Kristína
Gupta, Anindya
Frimmel, Hans
Sintorn, Ida-Maria
Bengtsson, Ewert
Smedby, Örjan
statement of authorship
Kristína Lidayová, Anindya Gupta, Hans Frimmel, Ida-Maria Sintorn, Ewert Bengtsson & Örjan Smedby
source
Medical Image : Understanding and Analysis, 21st Annual Conference, MIUA 2017 Edinburgh, UK, July 11–13, 2017 : Proceedings
location of publication
Cham
publisher
Springer
year of publication
2017
pages
p. 182-194
series
Communications in computer and information science ; 723
conference name, date
Medical Image : Understanding and Analysis, 21st Annual Conference, MIUA 2017, 11–13 July 2017
conference location
Edinburgh, UK
url
https://doi.org/10.1007/978-3-319-60964-5_16
subject term
klassifitseerimine
närvivõrgud
veresooned
angiograafia
skelett
Scopus
https://www.scopus.com/sourceid/17700155007
https://www.scopus.com/record/display.uri?eid=2-s2.0-85022182486&origin=inward&txGid=285f3a80bf67d0ed5a00879adfd06a4b
WOS
https://www.webofscience.com/wos/woscc/full-record/WOS:000770548800016
quartile
Q3
category (general)
Mathematics
Matemaatika
Computer science
Arvutiteadus
category (sub)
Mathematics. General mathematics
Matemaatika. Üldmatemaatika
Computer science. General computer science
Arvutiteadus. Üldine arvutiteadus
keyword
classification
convolutional neural networks
CT angiography
vascular skeleton
ISSN
1865-0929
ISBN
978-331960963-8
notes
Bibliogr.: 14 ref
scientific publication
teaduspublikatsioon
classifier
3.1
TalTech department
Thomas Johann Seebecki elektroonikainstituut
language
inglise