Abstract:
Breast cancer is the only cancer that is considered universal among women worldwide. Breast cancer is the most common cancer in American women, except for skin cancers. Currently, the average risk of a woman in the United States developing breast cancer sometime in her life is about 12%.
Breast cancer is sometimes found after symptoms appear, but many women with breast cancer have no symptoms. This is why regular breast cancer screening is so
important. There is no sure way to prevent breast cancer.
Thus, early detection and treatment are crucial in minimizing breast cancer related deaths. Due to the inherent nature of ultrasound imaging such as uneven speckle patterns, no fixed threshold values, anisotropy and signal drop-out bio medical image processing is a challenging task. Automatic segmentation of BUS is very difficult due to uneven shape and imprecise boundary of breast lesions.
In order to improve the problem prevalent in the existing methods, a complete qualitative analysis of Breast ultrasound (BUS) images for tumor detection is proposed in this thesis. The method involves four steps – (a) Speckle reduction using different filters, (b) Strain estimation by various methods, (c) 2D search for displacement and then application of 1.5D adaptive stretching and (d) Image segmentation for lesion detection.
Description:
Supervised by Prof. Dr. Md. Ashraful Hoque Head,
Department of Electrical and
Electronic Engineering,
Islamic University of Technology(IUT)
Board Bazar, Gazipur-1704, Bangladesh.
