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An IVUS image-based approach for improvement of coronary plaque characterization

Abstract : Virtual Histology-Intravascular Ultrasound (VH-IVUS) is widely used for studying atherosclerosis plaque composition. However, one of the main limitations of the VH-IVUS relates to its dependence to the lectrocardiogram (ECG)-gated acquisition. To overcome this limitation, this paper proposes a robust image-based approach for characterization of the plaques using IVUS images. The proposed method consists of three main steps of (1) shadow detection: as an efficient preprocessing step to identify and remove acoustic shadow regions; (2) feature extraction: a combination of gray-scale based features and textural descriptors; and (3) classification: to classify each pixel into one of the three classes (calcium, necrotic core and fibro-fatty). In order to evaluate the efficiency of the proposed algorithm two in-vivo and ex-vivo data sets are considered. The kappa values of 0.639 on in-vivo and 0.628 on ex-vivo tests with VH-IVUS and the histology images labeled by the experts respectively indicate the effectiveness of the proposed algorithm.
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Submitted on : Wednesday, September 3, 2014 - 5:15:36 PM
Last modification on : Thursday, January 6, 2022 - 11:38:04 AM




Arash Taki, Alireza Roodaki, S.-K. Setarehdan, Sara Avansari, Gozde Unal, et al.. An IVUS image-based approach for improvement of coronary plaque characterization. Computers in Biology and Medicine, Elsevier, 2013, 43 (4), pp.268-280. ⟨10.1016/j.compbiomed.2012.12.008⟩. ⟨hal-01060519⟩



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