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

Kichun Lee; Jun-Hee Heu; Jieun Kim

doi:10.1117/1.JEI.22.3.033010

12 August 2013 Support vector machine-based boundary recovery of a medical image segment in low resolution

Kichun Lee, Jun-Hee Heu, Jieun Kim

Author Affiliations +

Journal of Electronic Imaging, Vol. 22, Issue 3, 033010 (August 2013). https://doi.org/10.1117/1.JEI.22.3.033010

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

Published: 12 August 2013

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