Mass screening and feature reserved compression in a computer-aided system for mammograms

Sheng Chih Yang, Yi Jhen Lin, Pau-Choo Chung, Giu Cheng Hsu, Chien Shen Lo

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

5 Citations (Scopus)

Abstract

This paper presents a computer-aided prescreening and storage system, which automatically prescreens the mass regions from mammograms and based on the results, performs a progressive compression in the storage. This is performed in two subsystems called mass screening subsystem and mass feature reserved compression subsystem. In the first subsystem, breast region is firstly extracted from images, followed by Gradient Enhancement and Median Filtering. Then, 19 texture features are calculated from 32*32 pixel blocks on the extracted breast region, and suboptimal feature subset is extracted. Then SVM classifier is employed for classifying the regions into mass, breast without masses and background. In the second subsystem, Vector Quantization GHNN (Grey-based Competitive Hopfield neural network) is applied on the three regions with different compression rates according their importance factors so as to reserve important features and simultaneously reduce the size of mammograms for storage efficiency.

Original languageEnglish
Title of host publication2008 International Joint Conference on Neural Networks, IJCNN 2008
Pages3779-3786
Number of pages8
DOIs
Publication statusPublished - 2008 Nov 24
Event2008 International Joint Conference on Neural Networks, IJCNN 2008 - Hong Kong, China
Duration: 2008 Jun 12008 Jun 8

Publication series

NameProceedings of the International Joint Conference on Neural Networks

Other

Other2008 International Joint Conference on Neural Networks, IJCNN 2008
CountryChina
CityHong Kong
Period08-06-0108-06-08

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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