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Debris removal in Pap-smear images
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
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2013 (English)In: Computer Methods and Programs in Biomedicine, ISSN 0169-2607, E-ISSN 1872-7565, Vol. 111, no 1, 128-138 p.Article in journal (Refereed) Published
Abstract [en]

Since its introduction in the 1940s the Pap-smear test has helped reduce the incidence of cervical cancer dramatically in countries where regular screening is standard. The automation of this procedure is an open problem that has been ongoing for over fifty years without reaching satisfactory results. Existing systems are discouragingly expensive and yet they are only able to make a correct distinction between normal and abnormal samples in a fraction of cases. Therefore, they are limited to acting as support for the cytotechnicians as they perform their manual screening. The main reason for the current limitations is that the automated systems struggle to overcome the complexity of the cell structures. Samples are covered in artefacts such as blood cells, overlapping and folded cells, and bacteria, that hamper the segmentation processes and generate large number of suspicious objects. The classifiers designed to differentiate between normal cells and pre-cancerous cells produce unpredictable results when classifying artefacts. In this paper, we propose a sequential classification scheme focused on removing unwanted objects, debris, from an initial segmentation result, intended to be run before the actual normal/abnormal classifier. The method has been evaluated using three separate datasets obtained from cervical samples prepared using both the standard Pap-smear approach as well as the more recent liquid based cytology sample preparation technique. We show success in removing more than 99% of the debris without loosing more than around one percent of the epithelial cells detected by the segmentation process.

Place, publisher, year, edition, pages
2013. Vol. 111, no 1, 128-138 p.
Keyword [en]
Debris removal, Pap-smear, Cervical cancer screening, LBC
National Category
Medical Image Processing
URN: urn:nbn:se:uu:diva-204092DOI: 10.1016/j.cmpb.2013.02.008ISI: 000320346400013OAI: oai:DiVA.org:uu-204092DiVA: diva2:637804
Available from: 2013-07-22 Created: 2013-07-22 Last updated: 2014-01-24Bibliographically approved
In thesis
1. Image Analysis in Support of Computer-Assisted Cervical Cancer Screening
Open this publication in new window or tab >>Image Analysis in Support of Computer-Assisted Cervical Cancer Screening
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Cervical cancer is a disease that annually claims the lives of over a quarter of a million women. A substantial number of these deaths could be prevented if population wide cancer screening, based on the Papanicolaou test, were globally available. The Papanicolaou test involves a visual review of cellular material obtained from the uterine cervix. While being relatively inexpensive from a material standpoint, the test requires highly trained cytology specialists to conduct the analysis. There is a great shortage of such specialists in developing countries, causing these to be grossly overrepresented in the mortality statistics. For the last 60 years, numerous attempts at constructing an automated system, able to perform the screening, have been made. Unfortunately, a cost-effective, automated system has yet to be produced.

In this thesis, a set of methods, aimed to be used in the development of an automated screening system, are presented. These have been produced as part of an international cooperative effort to create a low-cost cervical cancer screening system. The contributions are linked to a number of key problems associated with the screening: Deciding which areas of a specimen that warrant analysis, delineating cervical cell nuclei, rejecting artefacts to make sure that only cells of diagnostic value are included when drawing conclusions regarding the final diagnosis of the specimen. Also, to facilitate efficient method development, two methods for creating synthetic images that mimic images acquired from specimen are described.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2013. 95 p.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1106
Image analysis, cervical cancer, pap-smear, synthetic images, screening, image processing, cytometry
National Category
Medical Image Processing
Research subject
Computerized Image Processing
urn:nbn:se:uu:diva-212518 (URN)978-91-554-8828-4 (ISBN)
Public defence
2014-02-07, Room 2446, Polacksbacken, Lägerhyddsvägen 2, Uppsala, 13:15 (English)
Vinnova, 2008-01712Swedish Research Council, 2008-2738
Available from: 2014-01-16 Created: 2013-12-11 Last updated: 2014-07-21

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