Texture-based classification of atherosclerotic carotid plaques

By C. Christodoulou, Constantinos S. Pattichis, Marios Pantziaris, Andrew Nicolaides. IEEE Transactions on Medical Imaging, 2003

335 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine

View Paper: https://www.semanticscholar.org/paper/2d8ad2e93fc8032f0996e9b6543dc7f2fb305aaf

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In Computational Theory and Mathematics

In Computer Vision and Pattern Recognition

In Pulmonary and Respiratory Medicine

Citations in the corpus

Multiscale Amplitude-Modulation Frequency-Modulation (AM–FM) Texture Analysis of Multiple Sclerosis in Brain MRI Images (2011, methodology): “volved the use of 274 images (see also [29], 137 asymptomatic subjects and 137 patients).”
Comparative evaluation of despeckle filtering in ultrasound imaging of the carotid artery (2005, methodology): “The most discriminant features are the ones with the highest distance values [38].”
Multiscale Amplitude-Modulation Frequency-Modulation (AM–FM) Texture Analysis of Ultrasound Images of the Intima and Media Layers of the Carotid Artery (2011, methodology): “For these cases, the user of the proposed system may run the snakes initialization procedure again in order to estimate the correct initial snake contour, and during the snakes deformation the user may interact and manually correct the contour [5], [25].”
Ultrasound image segmentation: a survey (2006, background): “…and discrimination studies of liver tissues [219]–[229] breast masses [74]–[79], [84], [85], [194], [230]–[238], carotid plaques [239], [240], coronary plaques [241], [242], myocardial tissues [66], [243], the thyroid gland [244], [245], ovarian masses [163] and prostate tissues [246],…”