Breast cancer is a major medical concern for people everywhere. The advent of
deep learning introduces options to assist medical personnel in combating the
disease. In this work we used deep learning methods to predict the presence of
breast cancer on patients with tumorous lesions. We develop a pipeline that
includes a segmentation and classification model. The first determines the
location of the lesion and the second determines weather the lesion is benign
or malign. Our goal was to reach the performance of contemporary models
in the field and test our approach on a custom dataset of mammographic
images. Despite initial success with our classification model, the evaluation
of the final pipeline did not achieve the desired results. The reason for this is
the segmentation model, which failed to detect several potential lesions in
the input image.
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