title: Estimating cell count and distribution in labeled histological samples using incremental cell search.
abstract: Cell proliferation is critical to the outgrowth of biological structures including the face and limbs. This cellular process has traditionally been studied via sequential histological sampling of these tissues. The length and tedium of traditional sampling is a major impediment to analyzing the large datasets required to accurately model cellular processes. Computerized cell localization and quantification is critical for high-throughput morphometric analysis of developing embryonic tissues. We have developed the Incremental Cell Search (ICS), a novel software tool that expedites the analysis of relationships between morphological outgrowth and cell proliferation in embryonic tissues. Based on an estimated average cell size and stain color, ICS rapidly indicates the approximate location and amount of cells in histological images of labeled embryonic tissue and provides estimates of cell counts in regions with saturated fluorescence and blurred cell boundaries. This capacity opens the door to high-throughput 3D and 4D quantitative analyses of developmental patterns.
authors: Department of Computer Science, Faculty of Science, Memorial University of Newfoundland, St John's, NL, Canada A1B 3X5.
authors: Oscar E
authors: OE
authors: Meruvia-Pastor
authors: Jung
authors: J
authors: Soh
authors: Eric J
authors: EJ
authors: Schmidt
authors: Julia C
authors: JC
authors: Boughner
authors: Mei
authors: M
authors: Xiao
authors: Heather A
authors: HA
authors: Jamniczky
authors: Benedikt
authors: B
authors: Hallgrímsson
authors: Christoph W
authors: CW
authors: Sensen