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Local elastic matching and pattern recognition in MR mammography
Author(s) -
Fischer Harald,
Otte Matthias,
EhrittBraun Claudia,
Laubenberger Jörg,
Hennig Jürgen
Publication year - 1999
Publication title -
international journal of imaging systems and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.359
H-Index - 47
eISSN - 1098-1098
pISSN - 0899-9457
DOI - 10.1002/(sici)1098-1098(1999)10:2<199::aid-ima10>3.0.co;2-q
Subject(s) - contrast (vision) , computer science , mammography , matching (statistics) , artificial intelligence , breast cancer , computer vision , dynamics (music) , magnetic resonance imaging , motion (physics) , pattern recognition (psychology) , cancer , radiology , medicine , physics , pathology , acoustics
Contrast agent‐enhanced magnetic resonance (MR) mammography is a highly sensitive method in breast cancer detection. The inflow of contrast agent is tracked to classify tissue as malignant or benign. In this article, we introduce approaches to overcome two of the most prominent problems in MR mammography: (a) variability in contrast agent dynamics, and (b) motion of the patient during data acquisition. The variability of contrast agent dynamics is considered using data‐driven analysis based on self‐organizing maps. Motion during data acquisition is handled by means of a fast local elastic matching algorithm. © 1999 John Wiley & Sons, Inc. Int J Imaging Syst Technol, 10, 199–206, 1999