Open AccessLargest contour segmentation: A tool for the localization of spots in confocal images
Author(s) -
Manders E. M. M.,
Hoebe R.,
Strackee J.,
Vossepoel A. M.,
Aten J. A.
Publication year - 1996
Publication title -
cytometry
Language(s) - English
Resource type - Journals
eISSN - 1097-0320
pISSN - 0196-4763
DOI - 10.1002/(sici)1097-0320(19960101)23:1<15::aid-cyto3>3.0.co;2-l
Subject(s) - voxel , centroid , artificial intelligence , segmentation , spots , computer vision , confocal , computer science , position (finance) , boundary (topology) , pattern recognition (psychology) , image segmentation , domain (mathematical analysis) , mathematics , optics , physics , chemistry , mathematical analysis , finance , economics
An accurate determination of the 3‐D positions of multiple spots in images obtained by confocal microscopy is essential for the investigation of the spatial distribution of specific components or processes in biological specimens. The position of the centroid, as an estimator for the position of a spot, can be calculated on the basis of all voxels that belong to the domain of the spot. For this calculation a domain that defines which voxels belong to the spot must be delimited. To create a boundary for a domain we developed a 3‐D image segmentation procedure: the largest contour segmentation (LCS). This procedure is based on an iterative region‐growing procedure around each local maximum of intensity. By means of this procedure the position of each spot was determined accurately and automatically. Qualities of the procedure were evaluated by means of simulated test‐images as well as 3‐D images of real biological specimens. © 1996 Wiley‐Liss, Inc.