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Journal of Electronic Imaging

Support vector machine-based boundary recovery of a medical image segment in low resolution
Author(s): Kichun Lee; Jun-Hee Heu; Jieun Kim
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Paper 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.

Paper Details

Date Published: 12 August 2013
PDF: 10 pages
J. Electron. Imag. 22(3) 033010 doi: 10.1117/1.JEI.22.3.033010
Published in: Journal of Electronic Imaging Volume 22, Issue 3
Show Author Affiliations
Kichun Lee, Hanyang Univ. (Korea, Republic of)
Jun-Hee Heu, SK TelecomVideo Technology Lab. (Korea, Republic of)
Jieun Kim, Royal College of Art (United Kingdom)

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