Classification of mammorgraphic microcalcification clusters using a combination of topological and location modelling

Oluwaseun Ashiru, Reyer Zwiggelaar

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

3 Citations (Scopus)

Abstract

We have investigated the classification of micro-calcification clusters in mammograms by combining two existing approaches. One of the approaches involves extracting and using topological information (connectivity) about micro-calcification clusters as feature vectors to classify them as being benign or malignant. The other approach involves extracting and using location details of micro-calcification clusters (where they appear in a breast and/or mammogram) as feature vectors to classify them as being benign or malignant. We have investigated various aspects of both methods and their combination. Our initial results, based on MIAS and DDSM indicate no significant improvement over the topological approach on its own
Original languageEnglish
Title of host publication6th International Conference on Image Processing Theory
Subtitle of host publicationTools and Applications
EditorsM. Pietikainen, A. Hadid, M. B. Lopez
PublisherIEEE Press
ISBN (Print)978-146738910-5
DOIs
Publication statusPublished - 17 Jan 2017
Event6th International Conference on Image Processing Theory : Tools and Applications - Oulu, Finland
Duration: 12 Dec 201615 Dec 2016

Conference

Conference6th International Conference on Image Processing Theory
Abbreviated titleIPTA 2016
Country/TerritoryFinland
CityOulu
Period12 Dec 201615 Dec 2016

Keywords

  • topology
  • mammography
  • delta-sigma modulation
  • feature extraction
  • breast cancer

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