  Breast cancer ranks as the most prevalent form of cancer diagnosed in women,
and diagnosis faces several challenges, a change in the size, shape and
appearance of breasts, dense breast tissue, lumps or thickening in the breast
especially if in only one breast, lumps and nodules in the breast. The major
challenge that faces deep learning diagnosis of breast cancer was its shape,
size and position non-uniformity especially malignant cancer. This work
proposed a deep learning system that increased the accuracy of classification
of breast cancer types from ultrasound images. It reaches 99.29% accuracy,
exceeding other previous work. First, image processing was applied to in
enhance the quality of input images. Second, the image segmentation was
performed using U-Net architecture. Third, many features are extracted using
Mobilenet. Finally, the accuracy of proposed system was evaluated.
