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Ultrasound intima‐media thickness measurement of the carotid artery using ant colony optimization combined with a curvelet‐based orientation‐selective filter
Author(s) -
Li Hao,
Zhang Shijie,
Ma Rui,
Chen Huiren,
Xi Shui,
Zhang Jue,
Fang Jing
Publication year - 2016
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4943567
Subject(s) - artificial intelligence , curvelet , computer vision , speckle noise , ant colony optimization algorithms , robustness (evolution) , computer science , thresholding , speckle pattern , sobel operator , orientation (vector space) , image segmentation , ultrasound , segmentation , edge detection , pattern recognition (psychology) , image processing , mathematics , medicine , radiology , wavelet transform , image (mathematics) , wavelet , biochemistry , chemistry , geometry , gene
Purpose: Automatic measurement of the intima‐media thickness (IMT) from ultrasound carotid images is an important task in clinical diagnosis. Many computer‐based techniques for IMT measurement have been proposed to overcome the limits of manual segmentation. However, the robustness of the algorithms would be influenced by the inherent speckle noise of ultrasound image. This paper proposed a curvelet guided ant colony optimization (CGACO) strategy that could achieve satisfied accuracy for IMT measurement with improved robustness to noise.Methods: The curvelet‐based orientation‐selective (CBOS) filter was first introduced for speckle removal and edge enhancement. Different from conventional methods, CBOS filter processes the curvelet coefficients by orientations rather than by magnitude. Then, a specially designed two‐leg ant colony optimization technique, combined with Otsu thresholding and Sobel edge detector, was proposed as a novel segmentation method to extract the media‐adventitia (MA) and the lumen‐intima (LI) boundaries. Finally, a coupled snake model was employed to further smooth the contours of MA and LI.Results: In addition to 224 carotid artery images acquired from 34 participants, simulated speckled images with nine levels of noise were also included in the database. The mean absolute distance errors of CGACO for LI interface tracings, MA interface tracings, and IMT measurements were 0.030 ± 0.027, 0.039 ± 0.036, and 0.041 ± 0.036 mm, respectively. Besides, CGACO had a correlation coefficient as high as 0.992 and a bias as low as −0.008. All these measures were comparable to or better than a previous technique and the manual segmentation. On the other hand, CGACO had the highest success rate of 98.7% in the segmentation of real data. It also maintained a much higher success rate in the segmentation of simulated images with different levels of speckle noise.Conclusions: The proposed technique showed accurate IMT measurement results. Furthermore, benefiting from the CBOS filter, the robustness to noise of the algorithm was substantially improved. Therefore, CGACO could provide a reliable way to segment the carotid artery from ultrasound images and could be used in clinical practice of IMT measurement, particularly in early atherosclerotic stages.