Flinders University Flinders Academic Commons

Flinders Academic Commons >
Flinders Digital Archive >
Science and Engineering >
Computer Science, Engineering and Mathematics  >
Computer Science, Engineering and Mathematics - Collected Works >

Please use this identifier to cite or link to this item: http://hdl.handle.net/2328/25728

Title: Mammographic Mass Detection with Statistical Region Merging
Authors: Bajger, Mariusz
Ma, Fei
Williams, Simon
Bottema, Murk Jan
Keywords: Segmentation
Mass detection
Statistical region merging
Issue Date: 2010
Publisher: Institute of Electrical and Electronics Engineers Computer Society (IEEE Publishing)
Citation: Bajger, M., Ma, F., Williams, S. and Bottema, M. 2010. Mammographic Mass Detection with Statistical Region Merging. 2010 International Conference on Digital Image Computing: Techniques and Applications (DICTA), 27-32.
Abstract: An automatic method for detection of mammographic masses is presented which utilizes statistical region merging for segmentation (SRM) and linear discriminant analysis (LDA) for classification. The performance of the scheme was evaluated on 36 images selected from the local database of mammograms and on 48 images taken from the Digital Database for Screening Mammography (DDSM). The Az value (area under the ROC curve) for classifying each region was 0.90 for the local dataset and 0.96 for the images from DDSM. Results indicate that SRM segmentation can form part of an robust and efficient basis for analysis of mammograms.
URI: http://hdl.handle.net/2328/25728
ISSN: 9781424488162
Appears in Collections:Computer Science, Engineering and Mathematics - Collected Works

Files in This Item:

File Description SizeFormat
Bajger Mammographic.pdf394.01 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.


Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback