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Cluster detection in cytology images using the cellgraph method
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2012 (English)In: Information Technology in Medicine and Education (ITME), 2012 International Symposium, 2012, 923-927 p.Conference paper (Refereed)
Abstract [en]

Automated cervical cancer detection system is primarily based on delineating the cell nuclei and analyzing their textural and morphometric features for malignant characteristics. The presence of cell clusters in the slides have diagnostic value, since malignant cells have a greater tendency to stick together forming clusters than normal cells. However, cell clusters pose difficulty in delineating nucleus and extracting features reliably for malignancy detection in comparison to free lying cells. LBC slide preparation techniques remove biological artifacts and clustering to some extent but not completely. Hence cluster detection in automated cervical cancer screening becomes significant. In this work, a graph theoretical technique is adopted which can identify and compute quantitative metrics for this purpose. This method constructs a cell graph of the image in accordance with the Waxman model, using the positional coordinates of cells. The computed graph metrics from the cell graphs are used as the feature set for the classifier to deal with cell clusters. It is a preliminary exploration of using the topological analysis of the cellgraph to cytological images and the accuracy of classification using SVM showed that the results are well suited for cluster detection.

Place, publisher, year, edition, pages
2012. 923-927 p.
, Proceedings of 2012 International Symposium on Information Technologies in Medicine and Education, ITME 2012, 2
Keyword [en]
adjacency matrix, cell cluster, cellgraph, cervical cancer, graph metrics, support vector machine, waxman model
National Category
Medical Image Processing
URN: urn:nbn:se:uu:diva-186823DOI: 10.1109/ITiME.2012.6291454ISBN: 978-1-4673-2109-9OAI: oai:DiVA.org:uu-186823DiVA: diva2:575897
2012 International Symposium on Information Technologies in Medicine and Education, ITME 2012, 3 August 2012 through 5 August 2012, Hokodate, Hokkaido, Japan
Available from: 2012-12-11 Created: 2012-11-29 Last updated: 2012-12-11Bibliographically approved

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Malm, PatrikBengtsson, Ewert
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Division of Visual Information and InteractionComputerized Image Analysis and Human-Computer Interaction
Medical Image Processing

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