Automated lesion detection in dynamic contrast enhanced magnetic resonance imaging of breast

Xi Liang; Romamohanarao Kotagiri; Helen Frazer; Qing Yang

doi:10.1117/12.2076234

20 March 2015 Automated lesion detection in dynamic contrast enhanced magnetic resonance imaging of breast

Xi Liang, Romamohanarao Kotagiri, Helen Frazer, Qing Yang

Proceedings Volume 9414, Medical Imaging 2015: Computer-Aided Diagnosis; 94141X (2015) https://doi.org/10.1117/12.2076234
Event: SPIE Medical Imaging, 2015, Orlando, Florida, United States

Abstract

We propose an automated method in detecting lesions to assist radiologists in interpreting dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) of breast. The aim is to highlight the suspicious regions of interest to reduce the searching time of the lesions and the possibility of radiologists overlooking small regions. In our method, we locate the suspicious regions by applying a threshold on essential features. The features are normalized to reduce the variation between patients. Support vector machine classifier is then applied to exclude normal tissues from these regions, using both kinetic and morphological features extracted in the lesions. In the evaluation of the system on 21 patients with 50 lesions, all lesions were successfully detected with 5.02 false positive regions per breast.

Citation Download Citation

Xi Liang, Romamohanarao Kotagiri, Helen Frazer, and Qing Yang "Automated lesion detection in dynamic contrast enhanced magnetic resonance imaging of breast", Proc. SPIE 9414, Medical Imaging 2015: Computer-Aided Diagnosis, 94141X (20 March 2015); https://doi.org/10.1117/12.2076234

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