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Statements

Subject Item
n2:RIV%2F00216305%3A26220%2F13%3APU104508%21RIV14-MPO-26220___
rdf:type
skos:Concept n14:Vysledek
dcterms:description
Object detection in ultrasound images is difficult problem mainly because of relatively low signal–to–noise ratio. This paper deals with object detection in the noisy ultrasound images using modified version of Viola–Jones object detector. The method describes detection of carotid artery longitudinal section in ultrasound B–mode images. The detector is primarily trained by AdaBoost algorithm and uses a cascade of Haar–like features as a classifier. The main contribution of this paper is a method for detection of carotid artery longitudinal section. This method creates cascade of classifiers automatically using genetic algorithms. We also created post–processing method that marks position of artery in the image. The proposed method was released as open–source software. Resulting detector achieved accuracy 96.29%. When compared to SVM classification enlarged with RANSAC (RANdom SAmple Consensus) method that was used for detection of carotid artery longitudinal section, works our method rea Object detection in ultrasound images is difficult problem mainly because of relatively low signal–to–noise ratio. This paper deals with object detection in the noisy ultrasound images using modified version of Viola–Jones object detector. The method describes detection of carotid artery longitudinal section in ultrasound B–mode images. The detector is primarily trained by AdaBoost algorithm and uses a cascade of Haar–like features as a classifier. The main contribution of this paper is a method for detection of carotid artery longitudinal section. This method creates cascade of classifiers automatically using genetic algorithms. We also created post–processing method that marks position of artery in the image. The proposed method was released as open–source software. Resulting detector achieved accuracy 96.29%. When compared to SVM classification enlarged with RANSAC (RANdom SAmple Consensus) method that was used for detection of carotid artery longitudinal section, works our method rea
dcterms:title
Evolutionary Improved Object Detector for Ultrasound Images Evolutionary Improved Object Detector for Ultrasound Images
skos:prefLabel
Evolutionary Improved Object Detector for Ultrasound Images Evolutionary Improved Object Detector for Ultrasound Images
skos:notation
RIV/00216305:26220/13:PU104508!RIV14-MPO-26220___
n14:predkladatel
n23:orjk%3A26220
n4:aktivita
n19:S n19:P
n4:aktivity
P(FR-TI4/151), S
n4:dodaniDat
n6:2014
n4:domaciTvurceVysledku
n5:2629291 n5:2140276 n5:9747397 n5:8261571
n4:druhVysledku
n12:D
n4:duvernostUdaju
n22:S
n4:entitaPredkladatele
n17:predkladatel
n4:idSjednocenehoVysledku
73822
n4:idVysledku
RIV/00216305:26220/13:PU104508
n4:jazykVysledku
n9:eng
n4:klicovaSlova
carotid artery, genetic algorithms, ultrasound, object detection, Viola–Jones detector.
n4:klicoveSlovo
n13:genetic%20algorithms n13:carotid%20artery n13:object%20detection n13:ultrasound n13:Viola%E2%80%93Jones%20detector.
n4:kontrolniKodProRIV
[E45A30340BC5]
n4:mistoKonaniAkce
Rome
n4:mistoVydani
Neuveden
n4:nazevZdroje
36th International Conference on Telecommunications and Signal processing
n4:obor
n11:IN
n4:pocetDomacichTvurcuVysledku
4
n4:pocetTvurcuVysledku
5
n4:projekt
n20:FR-TI4%2F151
n4:rokUplatneniVysledku
n6:2013
n4:tvurceVysledku
Güney, Selda Karásek, Jan Uher, Václav Burget, Radim Mašek, Jan
n4:typAkce
n7:WRD
n4:zahajeniAkce
2013-07-02+02:00
s:numberOfPages
5
n8:doi
10.1109/TSP.2013.6614002
n15:hasPublisher
Neuveden
n16:isbn
978-1-4799-0402-0
n21:organizacniJednotka
26220