Selection of Spatiotemporal Features in Breast MRI to Differentiate between Malignant and Benign Small Lesions Using Computer-Aided Diagnosis
Joint Authors
Meyer-Baese, U.
Plant, Claudia
Schlossbauer, T.
Meyer-Baese, Anke
Steinbruecker, F.
Source
Advances in Artificial Neural Systems
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-07-12
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
Automated detection and diagnosis of small lesions in breast MRI represents a challenge for the traditional computer-aided diagnosis (CAD) systems.
The goal of the present research was to compare and determine the optimal feature sets describing the morphology and the enhancement kinetic features for a set of small lesions and to determine their diagnostic performance.
For each of the small lesions, we extracted morphological and dynamical features describing both global and local shape, and kinetics behavior.
In this paper, we compare the performance of each extracted feature set for the differential diagnosis of enhancing lesions in breast MRI.
Based on several simulation results, we determined the optimal feature number and tested different classification techniques.
The results suggest that the computerized analysis system based on spatiotemporal features 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)
Steinbruecker, F.& Meyer-Baese, Anke& Plant, Claudia& Schlossbauer, T.& Meyer-Baese, U.. 2012. Selection of Spatiotemporal Features in Breast MRI to Differentiate between Malignant and Benign Small Lesions Using Computer-Aided Diagnosis. Advances in Artificial Neural Systems،Vol. 2012, no. 2012, pp.1-8.
https://search.emarefa.net/detail/BIM-508136
Modern Language Association (MLA)
Steinbruecker, F.…[et al.]. Selection of Spatiotemporal Features in Breast MRI to Differentiate between Malignant and Benign Small Lesions Using Computer-Aided Diagnosis. Advances in Artificial Neural Systems No. 2012 (2012), pp.1-8.
https://search.emarefa.net/detail/BIM-508136
American Medical Association (AMA)
Steinbruecker, F.& Meyer-Baese, Anke& Plant, Claudia& Schlossbauer, T.& Meyer-Baese, U.. Selection of Spatiotemporal Features in Breast MRI to Differentiate between Malignant and Benign Small Lesions Using Computer-Aided Diagnosis. Advances in Artificial Neural Systems. 2012. Vol. 2012, no. 2012, pp.1-8.
https://search.emarefa.net/detail/BIM-508136
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-508136