uu.seUppsala University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Closing Curves with Riemannian Dilation: Application to Segmentation in Automated Cervical Cancer Screening
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
2009 (English)In: Advances in Visual Computing / [ed] George Bebis et al., Berlin / Heidelberg: Springer , 2009, 337-346 p.Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we describe a nuclei segmentation algorithm for Pap smears that uses anisotropic dilation for curve closing. Edge detection methods often return broken edges that need to be closed to achieve a proper segmentation. Our method performs dilation using Riemannian distance maps that are derived from the local structure tensor field in the image. We show that our curve closing improve the segmentation along weak edges and significantly increases the overall performance of segmentation. This is validated in a thorough study on realistic synthetic cell images from our Pap smear simulator. The algorithm is also demonstrated on bright-field microscope images of real Pap smears from cervical cancer screening.

Place, publisher, year, edition, pages
Berlin / Heidelberg: Springer , 2009. 337-346 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 5875
Keyword [en]
Pap-smears, Riemannian dilation, Curve closing, Anisotropic dilation, Cell segmentation
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computerized Image Analysis
Identifiers
URN: urn:nbn:se:uu:diva-111501DOI: 10.1007/978-3-642-10331-5_32ISBN: 978-3-642-10330-8 (print)OAI: oai:DiVA.org:uu-111501DiVA: diva2:281437
Conference
ISVC
Available from: 2009-12-16 Created: 2009-12-16 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.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1106
Keyword
Image analysis, cervical cancer, pap-smear, synthetic images, screening, image processing, cytometry
National Category
Medical Image Processing
Research subject
Computerized Image Processing
Identifiers
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)
Opponent
Supervisors
Funder
Vinnova, 2008-01712Swedish Research Council, 2008-2738
Available from: 2014-01-16 Created: 2013-12-11 Last updated: 2014-07-21

Open Access in DiVA

No full text

Other links

Publisher's full texthttp://www.springerlink.com/content/mx3617731ql511r8/?p=e928a20d2c314195b9f613ba2ef6daf2&pi=0

Authority records BETA

Malm, Patrik

Search in DiVA

By author/editor
Malm, Patrik
By organisation
Computerized Image Analysis
Computer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 481 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf