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Learning-based initialization for correntropy-based level sets to segment atherosclerotic plaque in ultrasound images
This study proposes an automatic method for atherosclerotic plaque segmentation by using correntropy-based level sets (CLS) with learning-based initialization. We introduce the CLS model, containing the point-based local bias-field corrected image fitting method and correntropy-based distance measurement, to overcome the limitations of the ultrasound images. A supervised learning algorithm is employed to solve the automatic initialization problem of the variational methods. The proposed atherosclerotic plaque segmentation method is validated on 29 carotid ultrasound images, obtaining a Dice ratio of 90.6 ± 1.9% and an ove...
Source: Ultrasonics - September 4, 2022 Category: Physics Authors: Chunjun Qian Enjie Su Xinye Ni Source Type: research
