Small Lesions Evaluation Based on Unsupervised Cluster Analysis of Signal-Intensity Time Courses in Dynamic Breast MRI
Joint Authors
Wismueller, A.
Schlossbauer, T.
Meyer-Baese, A.
Lange, O.
Source
International Journal of Biomedical Imaging
Issue
Vol. 2009, Issue 2009 (31 Dec. 2009), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2010-04-01
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
An application of an unsupervised neural network-based computer-aided diagnosis (CAD) system is reported for the detection and characterization of small indeterminate breast lesions, average size 1.1 mm, in dynamic contrast-enhanced MRI.
This system enables the extraction of spatial and temporal features of dynamic MRI data and additionally provides a segmentation with regard to identification and regional subclassification of pathological breast tissue lesions.
Lesions with an initial contrast enhancement ≥50% were selected with semiautomatic segmentation.
This conventional segmentation analysis is based on the mean initial signal increase and postinitial course of all voxels included in the lesion.
In this paper, we compare the conventional segmentation analysis with unsupervised classification for the evaluation of signal intensity time courses for the differential diagnosis of enhancing lesions in breast MRI.
The results suggest that the computerized analysis system based on unsupervised clustering has the potential to increase the diagnostic accuracy of MRI mammography for small lesions and can be used as a basis for computer-aided diagnosis of breast cancer with MR mammography.
American Psychological Association (APA)
Meyer-Baese, A.& Schlossbauer, T.& Lange, O.& Wismueller, A.. 2010. Small Lesions Evaluation Based on Unsupervised Cluster Analysis of Signal-Intensity Time Courses in Dynamic Breast MRI. International Journal of Biomedical Imaging،Vol. 2009, no. 2009, pp.1-10.
https://search.emarefa.net/detail/BIM-463773
Modern Language Association (MLA)
Meyer-Baese, A.…[et al.]. Small Lesions Evaluation Based on Unsupervised Cluster Analysis of Signal-Intensity Time Courses in Dynamic Breast MRI. International Journal of Biomedical Imaging No. 2009 (2009), pp.1-10.
https://search.emarefa.net/detail/BIM-463773
American Medical Association (AMA)
Meyer-Baese, A.& Schlossbauer, T.& Lange, O.& Wismueller, A.. Small Lesions Evaluation Based on Unsupervised Cluster Analysis of Signal-Intensity Time Courses in Dynamic Breast MRI. International Journal of Biomedical Imaging. 2010. Vol. 2009, no. 2009, pp.1-10.
https://search.emarefa.net/detail/BIM-463773
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-463773