Robustness of two methods for segmenting salient features in screening mammograms

Ma Fei*, Mariusz Bajger, Murk J. Bottema

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

7 Citations (Scopus)

Abstract

The performance of two image segmentation methods are compared according to robustness of the segmentation to image distortion. This criterion is crucial for temporal analysis of screening mammograms where natural changes in the breast plus inherent deformation of soft tissue during image acquisition result in severe image registration problems. A method based on minimum spanning trees (MST) is found to be more robust to the distortions studied than a method based on adaptive pyramids (AP). Although segmentation leads to great differences in segmentation in distorted images for many components of low saliency, salient components (those of primary interest) are found to be segmented consistently regardless of distortion.

Original languageEnglish
Title of host publicationProceedings - Digital Image Computing Techniques and Applications
Subtitle of host publication9th Biennial Conference of the Australian Pattern Recognition Society, DICTA 2007
Pages112-117
Number of pages6
DOIs
Publication statusPublished - 2007
Externally publishedYes
EventAustralian Pattern Recognition Society (APRS) - Glenelg, SA, Australia
Duration: 3 Dec 20075 Dec 2007

Publication series

NameProceedings - Digital Image Computing Techniques and Applications: 9th Biennial Conference of the Australian Pattern Recognition Society, DICTA 2007

Conference

ConferenceAustralian Pattern Recognition Society (APRS)
Country/TerritoryAustralia
CityGlenelg, SA
Period3/12/075/12/07

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