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Content Provider | IEEE Xplore Digital Library |
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Author | Xiaoning Qian Byung-Jun Yoon |
Copyright Year | 2011 |
Description | Author affiliation: Texas A&M University, Department of Electrical & Computer Engineering, College Station, 77843, USA (Byung-Jun Yoon) || University of South Florida, Department of Computer Science & Engineering, Tampa, 33620, USA (Xiaoning Qian) |
Abstract | 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 be used for other image modalities with the presence of image inhomogeneity. |
Starting Page | 705 |
Ending Page | 708 |
File Size | 403389 |
Page Count | 4 |
File Format | |
ISBN | 9781457705380 |
ISSN | 15206149 |
e-ISBN | 9781457705397 |
e-ISBN | 9781457705373 |
DOI | 10.1109/ICASSP.2011.5946501 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2011-05-22 |
Publisher Place | Czech Republic |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Hidden Markov models Image segmentation Ultrasonic imaging Image edge detection Nonhomogeneous media Pixel Imaging ultrasound images hidden Markov model (HMM) contour finding |
Content Type | Text |
Resource Type | Article |
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