Detecting the Central Mass of a Spiculated Lesion Using Scale-Orientation Signatures

Reyer Zwiggelaar, Sue Astley, Christopher J. Taylor

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Potential malignancies in mammograms can be detected from subtle abnormalities in radiographic appearance. Radiologists fail to detect a significant proportion of such abnormalities, but it has been shown that their performance would improve if they were prompted with the locations of possible abnormalities [1].
Original languageEnglish
Title of host publicationDigital Mammography
Subtitle of host publicationNijmegen, 1998
EditorsNico Karssemeijer, Martin Thijssen, Jan Hendriks, Leon Erning
PublisherSpringer Nature
Pages63-70
Number of pages8
ISBN (Electronic)978-94-011-5318-8
ISBN (Print)978-0-7923-5274-7, 978-94-010-6234-3
DOIs
Publication statusPublished - 31 Oct 1998
Externally publishedYes

Publication series

NameComputational Imaging and Vision
PublisherSpringer Nature
Volume13
ISSN (Print)1381-6446

Keywords

  • classification
  • diagnosis
  • image processing
  • imaging
  • imaging techniques
  • performance

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