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@inproceedings{557690,
author = {Svoboda, David},
address = {Anaheim, Calgary, Zurich},
booktitle = {Visualization, Imaging, and Image Processing},
keywords = {Biomedical image segmentation; Adaptive thresholding; Gradient based thresholding; Region labeling},
language = {eng},
location = {Anaheim, Calgary, Zurich},
isbn = {0-88986-454-3},
pages = {430-434},
publisher = {ACTA Press},
title = {Towards a Fully Automated Tissue Cell Segmentation Method},
url = {http://www.actapress.com/PaperInfo.aspx?PaperID=18789&reason=500},
year = {2004}
}
TY - JOUR
ID - 557690
AU - Svoboda, David
PY - 2004
TI - Towards a Fully Automated Tissue Cell Segmentation Method
PB - ACTA Press
CY - Anaheim, Calgary, Zurich
SN - 0889864543
KW - Biomedical image segmentation
KW - Adaptive thresholding
KW - Gradient based thresholding
KW - Region labeling
UR - http://www.actapress.com/PaperInfo.aspx?PaperID=18789&reason=500
N2 - In this paper, an automatic method for tissue cell localization is proposed. It is based on the principle of adaptive thresholding. While the general adaptive thresholding method requires setting of some parameters by user, a novel algorithm chooses suitable thresholds and image division on its own. The resulting binary image is then submitted to a region labeling procedure. Each individual region is inspected and tested for suitability for further processing. Finally, each region is marked by one marker. Feasibility of this approach has already been successfully tested on 3D colon tissue images.
ER -
SVOBODA, David. Towards a Fully Automated Tissue Cell Segmentation Method. In \textit{Visualization, Imaging, and Image Processing}. Anaheim, Calgary, Zurich: ACTA Press, 2004, p.~430-434. ISBN~0-88986-454-3.
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