Classification of mammographic microcalcification and structural features using an artificial neural network

Atam P. Dhawan, Yateen S. Chitre, Myron Moskowitz, Eric Gruenstein

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

7 Scopus citations

Abstract

A set of image structure features which are defined using the second-order gray-level statistics is presented. These features provide information about the appearance and distribution of microcalcifications over the background of characteristic mammographic details. The image structure features are capable of extracting diagnostically useful information to help neural-network-based classification of mammographic microcalcifications. It is shown that the entropy feature has significant discriminating power for classification.

Original languageEnglish (US)
Title of host publicationProceedings of the Annual Conference on Engineering in Medicine and Biology
PublisherPubl by IEEE
Pages1105-1106
Number of pages2
Editionpt 3
ISBN (Print)0780302168
StatePublished - 1991
Externally publishedYes
EventProceedings of the 13th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Orlando, FL, USA
Duration: Oct 31 1991Nov 3 1991

Publication series

NameProceedings of the Annual Conference on Engineering in Medicine and Biology
Numberpt 3
Volume13
ISSN (Print)0589-1019

Other

OtherProceedings of the 13th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
CityOrlando, FL, USA
Period10/31/9111/3/91

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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