Comparison of multiresolution features for texture classification of carotid atherosclerosis from B-Mode ultrasound

Tsiaparas, NN; Golemati, S; Andreadis, I; Stoitsis, JS; Valavanis, I; Nikita, KS

dc.contributor.author	Tsiaparas, NN	en
dc.contributor.author	Golemati, S	en
dc.contributor.author	Andreadis, I	en
dc.contributor.author	Stoitsis, JS	en
dc.contributor.author	Valavanis, I	en
dc.contributor.author	Nikita, KS	en
dc.date.accessioned	2014-03-01T01:35:26Z
dc.date.available	2014-03-01T01:35:26Z
dc.date.issued	2011	en
dc.identifier.issn	1089-7771	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/21047
dc.subject	Carotid	en
dc.subject	texture	en
dc.subject	ultrasound	en
dc.subject	wavelet transforms	en
dc.subject.classification	Computer Science, Information Systems	en
dc.subject.classification	Computer Science, Interdisciplinary Applications	en
dc.subject.classification	Mathematical & Computational Biology	en
dc.subject.classification	Medical Informatics	en
dc.subject.other	Basis functions	en
dc.subject.other	Biomechanical factors	en
dc.subject.other	Carotid	en
dc.subject.other	Classification performance	en
dc.subject.other	Decomposition scheme	en
dc.subject.other	Different frequency	en
dc.subject.other	Feature selection	en
dc.subject.other	Gabor transform	en
dc.subject.other	Multi-resolution approach	en
dc.subject.other	Multi-resolution feature	en
dc.subject.other	Non-linear correlations	en
dc.subject.other	Probabilistic neural networks	en
dc.subject.other	Standard deviation	en
dc.subject.other	Stationary wavelet transforms	en
dc.subject.other	Subimages	en
dc.subject.other	Texture analysis	en
dc.subject.other	Texture classification	en
dc.subject.other	Texture features	en
dc.subject.other	Thresholding	en
dc.subject.other	ultrasound	en
dc.subject.other	Wavelet packets	en
dc.subject.other	Biomechanics	en
dc.subject.other	Discrete wavelet transforms	en
dc.subject.other	Feature extraction	en
dc.subject.other	Frequency bands	en
dc.subject.other	Neural networks	en
dc.subject.other	Support vector machines	en
dc.subject.other	Ultrasonics	en
dc.subject.other	Wavelet decomposition	en
dc.subject.other	Textures	en
dc.title	Comparison of multiresolution features for texture classification of carotid atherosclerosis from B-Mode ultrasound	en
heal.type	journalArticle	en
heal.identifier.primary	10.1109/TITB.2010.2091511	en
heal.identifier.secondary	http://dx.doi.org/10.1109/TITB.2010.2091511	en
heal.identifier.secondary	5629371	en
heal.language	English	en
heal.publicationDate	2011	en
heal.abstract	In this paper, a multiresolution approach is suggested for texture classification of atherosclerotic tissue from B-mode ultrasound. Four decomposition schemes, namely, the discrete wavelet transform, the stationary wavelet transform, wavelet packets (WP), and Gabor transform (GT), as well as several basis functions, were investigated in terms of their ability to discriminate between symptomatic and asymptomatic cases. The mean and standard deviation of the detail subimages produced for each decomposition scheme were used as texture features. Feature selection included 1) ranking the features in terms of their divergence values and 2) appropriately thresholding by a nonlinear correlation coefficient. The selected features were subsequently input into two classifiers using support vector machines (SVM) and probabilistic neural networks. WP analysis and the coiflet 1 produced the highest overall classification performance (90% for diastole and 75% for systole) using SVM. This might reflect WP's ability to reveal differences in different frequency bands, and therefore, characterize efficiently the atheromatous tissue. An interesting finding was that the dominant texture features exhibited horizontal directionality, suggesting that texture analysis may be affected by biomechanical factors (plaque strains). © 2006 IEEE.	en
heal.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC	en
heal.journalName	IEEE Transactions on Information Technology in Biomedicine	en
dc.identifier.doi	10.1109/TITB.2010.2091511	en
dc.identifier.isi	ISI:000286009500017	en
dc.identifier.volume	15	en
dc.identifier.issue	1	en
dc.identifier.spage	130	en
dc.identifier.epage	137	en