Artificial Intelligence for Automated Diagnosis of Breast Cancer

Study of an Artificial Intelligence Algorithm for the Classification of Digital Tomosynthesis Breast Images for Automated Breast Cancer Diagnosis

Mammography is a two-dimensional imaging technique which involves the tissues overlapping under the projective image; dense glandular tissue above or below the lesion can reduce the visibility of the lesion.

The trouble could be the interpretation of the image obtained which may lead to the inability to visualize a fist stage cancer and the probability that to a healthy person will be diagnosed a pathology that is not present (false positive). The introduction of an almost three-dimensional technique imaging called breast digital tomosynthesis (DBT) can overcome most limitations. In the last 5 years image analysis methods based on Artificial Intelligence (, AI) have also been massively introduced in breast cancer detection. The study is a prospective observational study based on Artificial intelligence whose the mail goal is to develop a method to identify a lesion.

Inclusion Criteria:

• Patients who refer to the Regina Elena for diagnostic mammography tests
• Informed consent

Exclusion Criteria:

• presence of prostheses, artifacts, outcomes of a study in the breast intervention under the study