A novel automatic seed point selection algorithm for breast ultrasound images

Region growing is a frequently used segmentation method for medical ultrasound images processing. The first step of region growing is selecting the seed point which is inside the breast lesion. Most of the region growing methods require manually selecting the seed point which needs human interaction. To make the segmentation completely automatic, we propose a new automatic seed point selecting method for region growing algorithm. The method is validated on our database with 105 ultrasound images with breast masses and it is compared with other automatic seed point selecting method on the same database. Quantitative experiment results show that our proposed method can successfully find the proper seed points for 95.2% of the US images in the database which is much more robust than other automatic seed point selection methods.

• Type: Conference
• Year: 2008
• Where: ICPR
• Authors: Juan Shan, Heng-Da Cheng, Yuxuan Wang
• Keywords: Automatic Seed Point, Computer Vision, ICPR 2008, Region Growing, Seed Point