Automated localization of malignant lesions in breast DCE-MRI

Dynamic contrast-enhanced magnetic resonance imaging (DCEMRI) is increasingly used for breast cancer assessment. Compared to mammography DCE-MRI provides higher sensitivity, however the specificity of DCE-MRI is variable. Continued e orts are focused on identifying distinguishing characteristics of malignant and benign lesions. DCE-MRI data analysis is time consuming and presents high inter- and intra-observer variability. The aim of this work is to propose an automated breast lesion localization system for DCE-MRI. Such a system can be used to support radiologists during DCE-MRI analysis, to facilitate pre-calculation of very computationally demanding features and to form the basis of a standalone computer aided diagnosis application. The proposed method initially segments the breast and uses a gentle adaboost classifier and features extracted from the relative signal enhancement to detect malignant lesions. Evaluation was performed on a dataset of 212 DCE-MRI studies from 126 patients with no sign of breast cancer and 86 patients with biopsy-proven annotated malignant lesions. The results obtained by our method are promising for clinical applications: 96% of the lesions of our study dataset were correctly detected at 10.4 false positives per patient without cancer.