Leila Bahreini - Department of Biomedical Engineering Science and Research Branch, Islamic Azad University Tehran, Iran
Emad Fatemizadeh - School of Electrical Engineering S Sharif University of Technology Tehran Iran
Masoumeh Gity - Medical Imaging Center Tehran University of Medical Science Tehran, Iran

The development of computer-aided diagnosis (CAD) for breast magnetic resonance (MR) images has encountered some big challenges. One of these challenges is related to breast lesion segmentation. Accurate segmentation of breast lesions has a vital role in other consequent applications such as feature extraction. Since malignant breast lesions typically appear with irregular borders and shapes in MR images whereas benign masses appear with more regular shapes, and smooth and lobulated borders, it seems that the accurate segmentation ofbreast lesion borders in MR images are important. To achieve this purpose, we have used the Gradient Vector Flow (GVF) snake segmentation method. This study included 52(33 malignant and 19 benign) histopathologically proven breast lesions and the stages of the proposed method are as follows: selecting the region of interest (ROI), segmentation using GVF, evaluation of GVF snake segmentation method. The results of GVF segmentation method in this study were satisfactory referred to the radiologist’s manual segmentation. The results showed the GVF snake segmentation method correctly segmented 97% of malignant lesion borders and 89.5% of benign lesion borders at the overlap threshold of 0.6. This indicates GVF snake segmentation method could provide us with a powerful method that can make an accurate segmentation in breast lesion borders.

breast DCE-MRI images; GVF snak; segmentation; computer-aided diagnosis