Document Detail


Fully automatic chromosome segmentation.
MedLine Citation:
PMID:  7851156     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
This paper is concerned with automatic segmentation of high resolution digitized metaphases. This includes automatic detection and rejection of interphase nuclei, stain debris, and other "noise"; automatic detection and segmentation of touching and overlapping chromosome clusters; and automatic rejection of cells which are evaluated as being incomplete, or incorrectly segmented, or where the cell is otherwise unsuitable for further analysis. In this paper, a rule-based approach is described which treats the cell as a whole rather than as a series of individual chromosomes or clusters. The rules adapt classification and segmentation parameters for each cell. Initially, different sets of parameters are chosen according to the staining method of the cells, and the goal of the segmentation. A chromosome number predictor is used to guide the adaptation of the parameters and to estimate the performance. The adaptation is iterative, and the self-adjustment will stop when either a satisfactory result is achieved or if the cell is rejected. The method was implemented on both a Sun workstation and a Cytoscan, a commercial machine for chromosome analysis. Seven hundred and thirteen cells from real data have been tested. A success rate of 90-95% has been achieved. The procedure has been implemented in an automatic aberration scoring system for routine use.
Authors:
L Ji
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Cytometry     Volume:  17     ISSN:  0196-4763     ISO Abbreviation:  Cytometry     Publication Date:  1994 Nov 
Date Detail:
Created Date:  1995-03-14     Completed Date:  1995-03-14     Revised Date:  2004-11-17    
Medline Journal Info:
Nlm Unique ID:  8102328     Medline TA:  Cytometry     Country:  UNITED STATES    
Other Details:
Languages:  eng     Pagination:  196-208     Citation Subset:  IM    
Affiliation:
MRC Human Genetics Unit, Western General Hospital, Edinburgh, Scotland, United Kingdom.
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MeSH Terms
Descriptor/Qualifier:
Chromosome Aberrations*
Humans
Image Processing, Computer-Assisted*
Karyotyping / methods*

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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