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JAKUBÍČEK, R. CHMELÍK, J. NECKÁŘ, J. KOLÁŘ, R.
Originální název
Automatic Segmentation of Myocardial Infarction in Rats Subjected to Regional Ischemia
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
The experimental and preclinical studies of ischemia and reperfusion on animal models usually evaluate the sizes of area at risk (AR) of infarction and infarct area (IA) as fundamental parameters. The authors usually don’t provide any detailed information about the image processing of their data, though the IA or AR segmentation is often challenging and prone to be expert-depending. Here, we describe a new approach for automatic IA and AR segmentation based on combination of Random Forest classifier and two-step pixel-wise k-means classification of image pixels. The evaluation has been performed on the set of 16 images from 8 rat hearts. We compared sizes of normal perfused tissues, viable area and IA (normalized to percentage of total area) obtained by our method with manually segmentation by biologist. We achieved mean absolute error of 2.59% with mean standard deviation of 1.61%.
Klíčová slova
image segmentation; infarct of myocard; histological image; heart; rat
Autoři
JAKUBÍČEK, R.; CHMELÍK, J.; NECKÁŘ, J.; KOLÁŘ, R.
Vydáno
12. 11. 2018
Nakladatel
Computing in Cardiology
Místo
Maastricht, Netherlands
ISSN
2325-887X
Periodikum
Ročník
45
Číslo
1
Stát
Spojené státy americké
Strany od
Strany do
4
Strany počet
URL
http://www.cinc.org/archives/2018/pdf/CinC2018-128.pdf
BibTex
@inproceedings{BUT151065, author="Roman {Jakubíček} and Jiří {Chmelík} and Jan {Neckář} and Radim {Kolář}", title="Automatic Segmentation of Myocardial Infarction in Rats Subjected to Regional Ischemia", booktitle="Computing in Cardiology 2018", year="2018", journal="Computing in Cardiology", volume="45", number="1", pages="1--4", publisher="Computing in Cardiology", address="Maastricht, Netherlands", doi="10.22489/CinC.2018.128", issn="2325-887X", url="http://www.cinc.org/archives/2018/pdf/CinC2018-128.pdf" }