Adaptive microcalcification detection in computer aided diagnosis

Ho Kyung Kang, Sung Min Kim, Nguyen N. Thanh, Yong Man Ro, Won Ha Kim

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

4 Scopus citations

Abstract

Microcalcification detection is an important part of early breast cancer detection. In this paper, we propose a microcalcification detection method in mammography CAD (computer-aided diagnosis) system. The proposed microcalcification detection includes two parts. One is adaptive mammogram enhancement algorithm using homomorphic filtering in wavelet. The filter parameters are determined by background characteristics. The other is multi-stage microcalcification detection method. To verify our algorithm, we performed experiments and measured free-response operation characteristics (FROC) curve. The results show that the proposed microcalcification detection method is more robust for fluctuating noisy environments.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsMarian Bubak, Geert Dick van Albada, Peter M. A. Sloot, Jack J. Dongarra
PublisherSpringer Verlag
Pages1110-1117
Number of pages8
ISBN (Print)3540221298
DOIs
StatePublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3039
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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