Wavelet octave energy for breast tumor classification on sonography: A new shape feature

Yueh Ching Liao, King Chu Hung, Cheng Tung Ku, Chin Feng Tsai, Shu Mei Guo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Infiltrative nature of lesions is a significant feature of malignant breast lesion in ultrasound images. Characterizing infiltrative nature is crucial for the realization of computer-aided diagnosis system. In this study, the infiltrative nature is regarded as an energy that produces irregularly & considerably local variances in a 1-D signal. The local variances can be enhanced by few high octave energies in 1-D discrete periodized wavelet transform (DPWT). A test dataset of breast sonograms with the lesion contour delineated by an experienced physician & two inexperienced students are built for feature efficacy evaluation. A high individual performance result implies that the proposed feature is well correlated with radiologist's perception & closer to match those in trained physician than morphometric parameters. Experimental results also reveal that with a great performance improvement, the proposed feature is suitable for the combination with some morphometric parameters.

Original languageEnglish
Title of host publicationProceedings of the 2009 IEEE International Conference on Networking, Sensing and Control, ICNSC 2009
Pages388-392
Number of pages5
DOIs
Publication statusPublished - 2009
Event2009 IEEE International Conference on Networking, Sensing and Control, ICNSC 2009 - Okayama, Japan
Duration: 2009 Mar 262009 Mar 29

Publication series

NameProceedings of the 2009 IEEE International Conference on Networking, Sensing and Control, ICNSC 2009

Other

Other2009 IEEE International Conference on Networking, Sensing and Control, ICNSC 2009
Country/TerritoryJapan
CityOkayama
Period09-03-2609-03-29

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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