Uterine calcifications segmentation and extraction from ultrasound images based on level set

Uterine-cancer is one of the most common malignant gynecological tumors, a serious threat to women health. The early symptoms of uterine cancer: its entire uterus is often accompanied by many clusters of fine, granular micro calcifications and individual grains appearance. Study on extracting calcifications has important significance in diagnosis of clinical medicine. Due to size and shape variability of calcifications, low contrast and the back ground ultrasonic image texture is un-homogeneous, so it leads to a result there exits no general segmentation algorithm in hand that is suitable for segmentation calcifications of uterus. We develop a method here which use level set to segment and extract calcifications. It is nice to segment and extract calcifications from uterus ultrasound images that are a group of database with typical characteristics from Ultrasound Diagnosis Department of Lanzhou local Hospital. It is helpful to make a correct scheme for patients.