This study proposes a nearly automatic ultrasound image segmentation algorithm for computer-aided diagnosis on breast
cancer. This method is realized in two phases, i.e., partition phase and edge grouping phase. The two phases are
implemented on the cell tessellation, which is generated by two-pass watershed transformation. With this unique
integration of the three ingredients, i.e., the partition and grouping phases and cell tessellation, it will be shown that the
breast lesion boundaries can be effectively and efficiently detected - even the lesion shape is very uneven. The proposed
algorithm can be served as the kernel of CAD system on breast ultrasound to improve the automation and performance.