Abstract #3827
Accurate Discrimination of Benign and Malignant Breast Cancer in Suspicious Tumors Based on Semi-Quantitative DCE-MRI Employing Support Vector Machine
Saeedeh Navaei Lavasani 1,2 , Masoomeh Gity 3 , Mahnaz Nabil 1,4 , Anahita Fathi Kazerooni 1,2 , and Hamidreza Saligheh Rad 1,2
1
Quantitative MR Imaging and Spectroscopy
Group, Research Center for Molecular and Cellular
Imaging, Tehran University of Medical Sciences, Tehran,
Iran,
2
Department of Medical Physics and
Biomedical Engineering, School of Medicine, Tehran
University of Medical Sciences, Tehran, Iran,
3
Department
of Radiology, School of Medicine, Tehran University of
Medical Sciences, Tehran, Iran,
4
Department
of Statistics, Tarbiat Modares University, Tehran, Iran
Dynamic Contrast Enhanced-Magnetic Resonance Imaging
(DCE-MRI) is widely used as sensitive tool in breast
tumor diagnosis. Interpretation of breast MRI requires
focusing not only on morphologic changes, but also on
the quantification of the areas with increased
enhancement. In this setting, accurate selection of
quantitative parameters and classification approach
could result in reliable tumor differentiation. We
propose an accurate approach, based on support vector
machine classification of dynamic features of suspicious
tumors within the breast to discriminate malignant or
benign breast lesions.
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