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Computer-aided diagnosis for diagnostically challenging breast lesions in DCE-MRI based on image registration and integration of morphologic and dynamic characteristics.
EURASIP J. Adv. Signal Process. 2013:157 (2013)
Diagnostically challenging lesions comprise both foci (small lesions) and non-mass-like enhancing lesions and pose a challenge to current computer-aided diagnosis systems. Motion-based artifacts lead in dynamic contrast-enhanced breast magnetic resonance to diagnostic misinterpretation; therefore, motion compensation represents an important prerequisite to automatic lesion detection and diagnosis. In addition, the extraction of pertinent kinetic and morphologic features as lesion descriptors is an equally important task. In the present paper, we evaluate the performance of a computer-aided diagnosis system consisting of motion correction, lesion segmentation, and feature extraction and classification. We develop a new feature extractor, the radial Krawtchouk moment, which guarantees rotation invariance. Many novel feature extraction techniques are proposed and tested in conjunction with lesion detection. Our simulation results have shown that motion compensation combined with Minkowski functionals and Bayesian classifier can improve lesion detection and classification.
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Publication type
Article: Journal article
Document type
Scientific Article
Keywords
Computer-aided Diagnosis ; Breast Mri ; Krawtchouk Moments ; Minkowski Functional ; Kinetics; Theoretic Cad-system ; Cancer ; Information ; Mammography ; Model
ISSN (print) / ISBN
1110-8657
e-ISSN
1687-0433
Quellenangaben
Volume: 2013,
Issue: 1,
Article Number: 157
Publisher
Springer
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Research Unit Scientific Computing (ASC)