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Contour Evolution Method for Precise Boundary Delineation of Medical Images

Natalia, F, Afriliana, N, Meidia, H, Young, JC and Sudirman, S Contour Evolution Method for Precise Boundary Delineation of Medical Images. In: TELKOMNIKA Telecommunication Computing Electronics and Control . (ICW-Telkomnika, 19 November 2019 - 22 November 2019, Yogyakarta, Indonesia). (Accepted)

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Abstract

Image segmentation is an important precursor to boundary delineation of medical images. One of the major challenges in applying automatic image segmentation in medical images is the imperfection in the imaging process which can result in inconsistent contrast and brightness levels, and low image sharpness and vanishing boundaries. Although recent advances in deep learning produce vast improvements in the quality of image segmentation, the accuracy of segmentation around object boundaries still requires improvement. We developed a new approach to contour evolution that is more intuitive but shares some common principles with the active contour model method. The method uses two concepts, namely the Boundary Grid and Sparse Boundary Representation, as an implicit and explicit representation of the boundary points. We tested our method using lumbar spine MRI images of 515 patients. The experiment results show that our method performs faster and more accurate and flexible than the Geodesic Active Contours.

Item Type: Conference or Workshop Item (Paper)
Additional Information: I/We hereby transfer the unlimited rights of publication of the above mentioned paper in whole to UAD. The copyright transfer covers the exclusive right to reproduce and distribute the article, including reprints, translations, photographic reproductions, micro form, electronic form (offline, online) or any other reproductions of similar nature.
Uncontrolled Keywords: Image Segmentation; Boundary Delineation; Contour Evolution; MRI Images
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
R Medicine > R Medicine (General)
Divisions: Computer Science
Publisher: Universitas Ahmad Dahlan
Date Deposited: 27 Sep 2019 10:38
Last Modified: 27 Sep 2019 10:38
URI: http://researchonline.ljmu.ac.uk/id/eprint/11399

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