Estimation of the digitized mammographic breast density by the histogram approach using the neural network

Sachiko Goto, Yoshiharu Azuma, Tetsuhiro Sumimoto, Yoshihiro Takeda, Shigeru Eiho

Research output: Contribution to conferencePaper

Abstract

Our aim was to improve the accuracy of classifying x-ray mammographic breast densities. The histogram approach using the neural network was used for the purpose of constructing a flexible system. In this study the phantom of the synthetic breast-equivalent resin material for the process of the A/D conversion of mammograms was employed. The digital values can offset the difference in characteristics between the mammography system, the unit, etc. Furthermore the features of our system use the neural network, and then tune the neural network by the histogram of the digital values and by the radiologists' and expert mammographers' assessment ability. Although there was an observer's bias, our system was able to classify the breast density automatically according to that observer. This is only possible if the observer has been trained to some extent and is capable of maintaining an objective assessment according to the assessment criteria.

Original languageEnglish
Publication statusPublished - Jan 1 2003
Event8th International Workshop on ADC Modelling and Testing, IWADC 2003 - Perugia, Italy
Duration: Sep 8 2003Sep 10 2003

Conference

Conference8th International Workshop on ADC Modelling and Testing, IWADC 2003
CountryItaly
CityPerugia
Period9/8/039/10/03

Keywords

  • Breast density
  • Classification
  • Histogram

ASJC Scopus subject areas

  • Modelling and Simulation

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    Goto, S., Azuma, Y., Sumimoto, T., Takeda, Y., & Eiho, S. (2003). Estimation of the digitized mammographic breast density by the histogram approach using the neural network. Paper presented at 8th International Workshop on ADC Modelling and Testing, IWADC 2003, Perugia, Italy.