Dynamic segmentation of breast tissue in digitized mammograms

J. T. Neyhart, M. D. Ciocco, R. Polikar, S. Mandayam, M. Tseng

Research output: Contribution to journalConference article

3 Citations (Scopus)

Abstract

The percentage of radiodense tissue in a mammogram has been used as a marker for determining breast cancer risk. In this paper, we present an image segmentation technique for identifying tissue and non-tissue regions of a digitized X-ray image. This procedure constitutes a vital step prior to subsequent processing for estimating the amount of radiodense tissue. The process involves the generation of a segmentation mask developed by using discrete wavelet transform techniques. Initial results have been promising, demonstrating the feasibility of the approach.

Original languageEnglish (US)
Pages (from-to)2669-2672
Number of pages4
JournalAnnual Reports of the Research Reactor Institute, Kyoto University
Volume3
StatePublished - Dec 1 2001
Event23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Istanbul, Turkey
Duration: Oct 25 2001Oct 28 2001

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Tissue
Discrete wavelet transforms
Image segmentation
Masks
X rays
Processing

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Mechanical Engineering

Cite this

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Dynamic segmentation of breast tissue in digitized mammograms. / Neyhart, J. T.; Ciocco, M. D.; Polikar, R.; Mandayam, S.; Tseng, M.

In: Annual Reports of the Research Reactor Institute, Kyoto University, Vol. 3, 01.12.2001, p. 2669-2672.

Research output: Contribution to journalConference article

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AU - Neyhart, J. T.

AU - Ciocco, M. D.

AU - Polikar, R.

AU - Mandayam, S.

AU - Tseng, M.

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N2 - The percentage of radiodense tissue in a mammogram has been used as a marker for determining breast cancer risk. In this paper, we present an image segmentation technique for identifying tissue and non-tissue regions of a digitized X-ray image. This procedure constitutes a vital step prior to subsequent processing for estimating the amount of radiodense tissue. The process involves the generation of a segmentation mask developed by using discrete wavelet transform techniques. Initial results have been promising, demonstrating the feasibility of the approach.

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