Noise resistance analysis of wavelet-based channel energy feature for breast lesion classification on ultrasound images

Yueh Ching Liao, Shu Mei Guo, King Chu Hung, Po Chin Wang, Tsung Lung Yang

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

1 Citation (Scopus)

Abstract

Wavelet-based channel energy with low cost and high efficacy is a valuable feature for the differential diagnoses between benign and malignant breast lesions. The new feature is a contour approach that generally suffers from lacking a reliable contour detection algorithm with convincing results due to extreme noise. For investigating a procedure suitable for clinical application, noise resistance capability of the new feature is evaluated in this study. The evaluation system consists of two snake-based contour detection algorithms associated with two pre-processes. These combinations can produce four test datasets of contour sonogram. Classification performance evaluation is based on a probabilistic neural network and a genetic algorithm used for distribution parameter determination.

Original languageEnglish
Title of host publicationAdvances in Multimedia Information Processing, PCM 2010 - 11th Pacific Rim Conference on Multimedia, Proceedings
Pages549-558
Number of pages10
EditionPART 2
DOIs
Publication statusPublished - 2010
Event11th Pacific Rim Conference on Multimedia, PCM 2010 - Shanghai, China
Duration: 2010 Sep 212010 Sep 24

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6298 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other11th Pacific Rim Conference on Multimedia, PCM 2010
CountryChina
CityShanghai
Period10-09-2110-09-24

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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