Document Detail


Mathematical modeling of the malignancy of cancer using graph evolution.
MedLine Citation:
PMID:  17462676     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
We report a novel computational method based on graph evolution process to model the malignancy of brain cancer called glioma. In this work, we analyze the phases that a graph passes through during its evolution and demonstrate strong relation between the malignancy of cancer and the phase of its graph. From the photomicrographs of tissues, which are diagnosed as normal, low-grade cancerous and high-grade cancerous, we construct cell-graphs based on the locations of cells; we probabilistically generate an edge between every pair of cells depending on the Euclidean distance between them. For a cell-graph, we extract connectivity information including the properties of its connected components in order to analyze the phase of the cell-graph. Working with brain tissue samples surgically removed from 12 patients, we demonstrate that cell-graphs generated for different tissue types evolve differently and that they exhibit different phase properties, which distinguish a tissue type from another.
Authors:
Cigdem Gunduz-Demir
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't     Date:  2007-03-27
Journal Detail:
Title:  Mathematical biosciences     Volume:  209     ISSN:  0025-5564     ISO Abbreviation:  Math Biosci     Publication Date:  2007 Oct 
Date Detail:
Created Date:  2007-09-18     Completed Date:  2007-12-06     Revised Date:  2009-11-11    
Medline Journal Info:
Nlm Unique ID:  0103146     Medline TA:  Math Biosci     Country:  United States    
Other Details:
Languages:  eng     Pagination:  514-27     Citation Subset:  IM    
Affiliation:
Department of Computer Engineering, Bilkent University, Ankara TR-06800, Turkey. gunduz@cs.bilkent.edu.tr
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MeSH Terms
Descriptor/Qualifier:
Algorithms
Brain Neoplasms / pathology*
Glioma / pathology
Humans
Image Processing, Computer-Assisted / methods*,  statistics & numerical data
Mathematics
Models, Biological*

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


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