Contour-based hidden Markov model to segment 2D ultrasound images

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Contour-based hidden Markov model to segment 2D ultrasound images
The segmentation of ultrasound images is challenging due to the difficulty of appropriate modeling of their appearance variations including speckle as well as signal dropout. We propose a novel automatic segmentation method for 2D cardiac ultrasound images based on hidden Markov models (HMMs). By directly exploiting the local image characteristics around contour points in images and integrating them into contour-based HMMs, we solve the segmentation problem by graph matching using an efficient dynamic programming algorithm. Due to the direct integration of local properties in our HMMs, our segmentation method automatically deals with inhomogeneity but avoids the complexities of explicit appearance modeling in classical Maximum A Posteriori (MAP) approaches. The optimization for contour extraction is straightforward and guarantees the global optimal results. We implemented our method to segment the endocardium in short-axis cardiac ultrasound images successfully. The method can also ...
Xiaoning Qian, Byung-Jun Yoon
Added 21 Aug 2011
Updated 21 Aug 2011
Type Journal
Year 2011
Authors Xiaoning Qian, Byung-Jun Yoon
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