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@inproceedings{700786,
author = {Hubený, Jan and Matula, Pavel},
address = {Anaheim, Calgary, Zurich},
booktitle = {Visualization Imaging and Image Processing},
keywords = {medical imaging fast Chan--Vese active contour segmentation},
language = {eng},
location = {Anaheim, Calgary, Zurich},
isbn = {0-88986-598-1},
pages = {189-196},
publisher = {ACTA Press},
title = {Fast and Robust Segmentation of Low Contrast Biomedical Images},
year = {2006}
}
TY - JOUR
ID - 700786
AU - Hubený, Jan - Matula, Pavel
PY - 2006
TI - Fast and Robust Segmentation of Low Contrast Biomedical Images
PB - ACTA Press
CY - Anaheim, Calgary, Zurich
SN - 0889865981
KW - medical imaging fast Chan--Vese active contour segmentation
N2 - This paper presents fast and robust algorithm for minimization of Chan--Vese energy functional. Proposed technique is based on recently published k-Means level set and threshold dynamics approximations of Chan--Vese functional. The approximation algorithms are combined in order to preserve their individual advantages and avoid their limitations. Hence, the proposed hybrid algorithm is robust and converges reasonably fast to steady state and is suitable for two-phase segmentation of low contrast biomedical data. A simple numerical scheme for threshold dynamics method is derived in the paper. Results of the hybrid algorithm that are better than results of both k-Means level set and threshold dynamics methods employed individually are presented.
ER -
HUBENÝ, Jan and Pavel MATULA. Fast and Robust Segmentation of Low Contrast Biomedical Images. In \textit{Visualization Imaging and Image Processing}. Anaheim, Calgary, Zurich: ACTA Press, 2006, p.~189-196. ISBN~0-88986-598-1.
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