Automated Boundary Detection of Breast Cancer in Ultrasound Images Using Watershed Algorithm

Automatic boundary detection is a challenging and one of the important issues in medical imaging. Contouring breast tumor lesions automatically may avail physicians for correct and faster diseases diagnoses. The ultrasound images are noisy, and boundary detection is a challenging task due to low contrast. The aim of this study is to implement the watershed algorithm in breast cancer ultrasound images to extract precise contours of the tumors. In this process, preprocessing filter reduces the noise by preserving the edges of the tumor lesion. Background and foreground area is calculated based on the threshold. A connected component graph is used to calculate region of interest based on the difference between background and foreground area. Finally, the watershed algorithm is applied to determine the contours of the tumor. In diagnosis applications, automatic lesion segmentation can save the time of a radiologist.