New Spatiotemporal Features for Improved Discrimination of Benign and Malignant Lesions in Dynamic Contrast-Enhanced-Magnetic Resonance Imaging of the Breast
Journal article, 2011

Objectives: The objective of this study was to measure the efficacy of 7 new spatiotemporal features for discriminating between benign and malignant lesions in dynamic contrast-enhanced-magnetic resonance imaging (MRI) of the breast. Methods: A total of 48 breast lesions from 39 patients were used: 25 malignant and 23 benign. Lesions were acquired using 1.5-T MRI machines in 3 different protocols. Two experiments were performed: (i) selection of the most discriminatory subset of features drawn from the new features and features from the literature and (ii) validation of classification performance of the selected subset of features. Results: Results of the feature selection experiment show that the subset comprising 2 of the new features is the most useful for automatic classification of suspicious lesions in the breast: (i) gradient correlation of maximum intensity and (ii) mean wash-in rate. Results of the validation experiment show that using these 2 features, unseen data can be classified with an area under the receiver operating characteristic curve of 0.91 ± 0.06. Conclusions: Results of the experiments suggest that suspicious lesions in dynamic contrast-enhanced-MRI of the breast can be classified, with high accuracy, using only 2 of the proposed spatiotemporal features. The selected features indicate heterogeneity of enhancement and speed of enhancement in a tissue. High values of these indicators are likely to be correlated with malignancy.


Yaniv Gal

Andrew Mehnert

Chalmers, Signals and Systems

Andrew Bradley

Dominic Kennedy

Stuart Crozier

Journal of Computer Assisted Tomography

0363-8715 (ISSN) 1532-3145 (eISSN)

Vol. 35 5 645-652

Areas of Advance

Life Science Engineering (2010-2018)

Subject Categories

Computer Vision and Robotics (Autonomous Systems)

Medical Image Processing



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