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Support vector machine-based boundary recovery of a medical image segment in low resolution

[+] Author Affiliations
Kichun Lee

Hanyang University, Department of Industrial Engineering, College of Engineering, 222 Wangsimni-ro, Seongdong-gu, Seoul 133-791, Republic of Korea

Jun-Hee Heu

SK TelecomVideo Technology Lab, Sunae dong, Bundang-gu, Seongnam-si, Gyeonggi-do 463-784, Republic of Korea

Jieun Kim

School of Design, Royal College of Art, Innovation Design Engineering, Kensington Gore, London Sw7 2EU, United Kingdom

J. Electron. Imaging. 22(3), 033010 (Aug 12, 2013). doi:10.1117/1.JEI.22.3.033010
History: Received December 6, 2012; Revised June 10, 2013; Accepted July 9, 2013
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Abstract.  A novel support vector machine (SVM)-based boundary recovery procedure for segmented medical objects in low-resolution images is proposed. The proposed procedure consists of two steps: segmentation and boundary interpolation steps. First, we initially estimate a coarse object region using an active contour-based segmentation method. Boundary recoveries from the first step exhibit considerably blocky artifacts and are easily misled by noise. Then, a reliable boundary recovery is achieved in the next step by the proposed support vector machines based interpolation scheme. In simulation, the proposed algorithm shows more reliable and better performance in the presence of noise and adequately preserves shapes and smooth boundaries that are essential characteristics of medical objects. We illustrate it using real-life data sets in regard to nonconvex tube detection in wall shear stress, lumen detection in carotid stenosis, micro-calcifications detection in digital mammography, and nonmedical fields as well.

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Citation

Kichun Lee ; Jun-Hee Heu and Jieun Kim
"Support vector machine-based boundary recovery of a medical image segment in low resolution", J. Electron. Imaging. 22(3), 033010 (Aug 12, 2013). ; http://dx.doi.org/10.1117/1.JEI.22.3.033010


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