AM-FM representations for the characterization of carotid plaque ultrasound Images
AuthorChristodoulou, Christodoulos I.
Pattichis, Constantinos S.
Pattichis, Marios S.
Nicolaïdes, Andrew N.
4th European Conference of the International Federation for Medical and Biological Engineering, ECIFMBE 2008
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Stroke is the third leading cause of death in the western world and a major cause of disability in adults. The objective of this work was to investigate the use of AM-FM representations for the characterization of carotid plaques ultrasound images for the identification of individuals with asymptomatic carotid stenosis at risk of stroke. To characterize the plaques using AM-FM features, we compute (i) the instantaneous amplitude, (ii) the instantaneous frequency magnitude and (iii) the instantaneous frequency angle in order to capture directional information. For each AM-FM feature, we compute the histograms over the plaque regions. The statistical K-nearest neighbour (KNN) classifier was implemented for the classification of the carotid plaques into symptomatic or asymptomatic using the leave-one-out methodology. Tests were carried out on a dataset of 274 carotid plaque ultrasound images (137 symptomatic + 137 asymptomatic), which showed that the AM-FM features performed slightly better than the traditional texture features and gave better results than simple histogram. Best results were obtained when a combination of the three AM-FM representations was used reaching a classification success rate of 71.5%. © 2009 Springer Berlin Heidelberg.