Comput Methods Programs Biomed - Understanding symptomatology of atherosclerotic plaque by image-based tissue characterization.

Tópicos

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Resumo

Characterization of carotid atherosclerosis and classification into either symptomatic or asymptomatic is crucial in terms of diagnosis and treatment planning for a range of cardiovascular diseases. This paper presents a computer-aided diagnosis (CAD) system (Atheromatic) that analyzes ultrasound images and classifies them into symptomatic and asymptomatic. The classification result is based on a combination of discrete wavelet transform, higher order spectra (HOS) and textural features. In this study, we compare support vector machine (SVM) classifiers with different kernels. The classifier with a radial basis function (RBF) kernel achieved an average accuracy of 91.7% as well as a sensitivity of 97%, and specificity of 80%. Thus, it is evident that the selected features and the classifier combination can efficiently categorize plaques into symptomatic and asymptomatic classes. Moreover, a novel symptomatic asymptomatic carotid index (SACI), which is an integrated index that is based on the significant features, has been proposed in this work. Each analyzed ultrasound image yields on SACI number. A high SACI value indicates that the image shows symptomatic and low value indicates asymptomatic plaques. We hope this SACI can support vascular surgeons during routine screening for asymptomatic plaques.

Resumo Limpo

character carotid atherosclerosi classif either symptomat asymptomat crucial term diagnosi treatment plan rang cardiovascular diseas paper present computeraid diagnosi cad system atheromat analyz ultrasound imag classifi symptomat asymptomat classif result base combin discret wavelet transform higher order spectra hos textur featur studi compar support vector machin svm classifi differ kernel classifi radial basi function rbf kernel achiev averag accuraci well sensit specif thus evid select featur classifi combin can effici categor plaqu symptomat asymptomat class moreov novel symptomat asymptomat carotid index saci integr index base signific featur propos work analyz ultrasound imag yield saci number high saci valu indic imag show symptomat low valu indic asymptomat plaqu hope saci can support vascular surgeon routin screen asymptomat plaqu

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