Header

UZH-Logo

Maintenance Infos

Robust 3D cell segmentation by local region growing in convex volumes - Zurich Open Repository and Archive


Pfister, Sabina Sara; Betizeau, Marion; Dehay, Colette; Douglas, Rodney (2013). Robust 3D cell segmentation by local region growing in convex volumes. Proceedings of the International Symposium on Biomedical Imaging:426-431.

Abstract

Clustering of cells is based on their expression profiles (either volume, average expression, standard deviation, sum, median or Pearson correlation coefficient). As an example, the hierarchical clustergram of median expression values was computed on 8343 cells in the germinal layers of monkey developing cerebral cortex stained for Pax6 (red), Tbr2 (blue), Ki67 (green), and nuclear staining DAPI. Cells where clustered with the standard k-means algorithm, whereby the number of clusters k=6 was determined empirically.

Abstract

Clustering of cells is based on their expression profiles (either volume, average expression, standard deviation, sum, median or Pearson correlation coefficient). As an example, the hierarchical clustergram of median expression values was computed on 8343 cells in the germinal layers of monkey developing cerebral cortex stained for Pax6 (red), Tbr2 (blue), Ki67 (green), and nuclear staining DAPI. Cells where clustered with the standard k-means algorithm, whereby the number of clusters k=6 was determined empirically.

Altmetrics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:2013
Deposited On:13 Feb 2014 14:08
Last Modified:05 Apr 2016 17:33
Publisher:Institute of Electrical and Electronics Engineers
ISSN:1945-7928
Additional Information:ISBN: 978-1-4673-6456-0
Publisher DOI:https://doi.org/10.1109/ISBI.2013.6556503

Download

Full text not available from this repository.
View at publisher

TrendTerms

TrendTerms displays relevant terms of the abstract of this publication and related documents on a map. The terms and their relations were extracted from ZORA using word statistics. Their timelines are taken from ZORA as well. The bubble size of a term is proportional to the number of documents where the term occurs. Red, orange, yellow and green colors are used for terms that occur in the current document; red indicates high interlinkedness of a term with other terms, orange, yellow and green decreasing interlinkedness. Blue is used for terms that have a relation with the terms in this document, but occur in other documents.
You can navigate and zoom the map. Mouse-hovering a term displays its timeline, clicking it yields the associated documents.

Author Collaborations