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Self-organizing map-based multi-thresholding on neural stem cells images.
MedLine Citation:
PMID:  19399542     Owner:  NLM     Status:  In-Process    
Abstract/OtherAbstract:
Automatic segmentation and tracking systems can be useful tools for biologists to monitor and understand the proliferation and the differentiation of neural stem cells. This paper applied the self-organizing map-based multi-thresholding on the neural stem cells images. Using local variance as the local spatial feature and quadtree decomposition as the sub-sampling method, inner-cell regions, cell borders and background can be roughly classified. Based on these results, proper foreground and background seeds were constructed for the seeded watershed segmentation and every single cell in a cell cluster can be segmented correctly. The results were also compared to the seeded watershed segmentation based on regional maxima method.
Authors:
Xiang Qian; Cheng Peng; Xueli Wang; Datian Ye
Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2009-04-28
Journal Detail:
Title:  Medical & biological engineering & computing     Volume:  47     ISSN:  1741-0444     ISO Abbreviation:  Med Biol Eng Comput     Publication Date:  2009 Jul 
Date Detail:
Created Date:  2009-06-01     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  7704869     Medline TA:  Med Biol Eng Comput     Country:  United States    
Other Details:
Languages:  eng     Pagination:  801-8     Citation Subset:  IM    
Affiliation:
Department of Biomedical Engineering, Tsinghua University, Beijing, China. qianxiang98@mails.tsinghua.edu.cn
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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