Abnormal masses in mammograms: Detection using scale-orientation signatures

Reyer Zwiggelaar, Christopher J. Taylor

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

4 Citations (Scopus)

Abstract

We describe a method for labelling image structure based on scale-orientation signatures. These signatures provide a rich and stable description of local structure and can be used as a basis for robust pixel classification. We use a multi-scale directional recursive median filtering technique to obtain local scale-orientation signatures. Our results show that the new method of representation is robust to the presence of both random and structural noise. We demonstrate application to synthetic images containing lines and blob-like features and to mammograms containing abnormal masses. Quantitative results are presented, using both linear and non-linear classification methods.
Original languageEnglish
Title of host publicationProceedings First International Conference Medical Image Computing and Computer-Assisted Intervention ─ MICCAI 1998
EditorsWilliam M. Wells, Alan Colchester, Scott Delp
PublisherSpringer Nature
Pages570-577
Number of pages8
ISBN (Electronic)978-3-540-49563-5
ISBN (Print)3540651365, 9783540651369
DOIs
Publication statusPublished - 02 Oct 1998
Externally publishedYes
Event1st International Conference on Medical Image Computing and Computer-Assisted Intervention - Cambridge, United States of America
Duration: 11 Oct 199813 Oct 1998

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1496
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st International Conference on Medical Image Computing and Computer-Assisted Intervention
Abbreviated titleMICCAI'98
Country/TerritoryUnited States of America
CityCambridge
Period11 Oct 199813 Oct 1998

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