Diagnosis of Breast Cancer Using the Harris Extraction Algorithm in the Processing of Medical Images

Identifying and demarcating the masses and diagnosing the disease in breast tissue is a serious challenge in diagnosing this cancer. Mammography is currently the most common method to diagnose breast cancer, in which incorrectly identifying the masses can lead to misdiagnosis or sampling of breast tissue. In this study, using feature extraction in medical image processing, we tried to make a diagnosis with better accuracy than in the past.

Mammographic image features were extracted using the Harris feature extraction algorithm. Mammographic images were analyzed using Matlab2019a software and ideal outputs were obtained.

Mammographic images were pre-processed and Harris algorithm was applied. In the output of the proposed algorithm, the accuracy and speed of detection of the algorithm were higher in comparison to other routine methods.

The purpose of extracting the Harris property is to make the raw data more usable for future statistical processing. it is expected that in the future, feature extraction will be more accurate, and more details will be provided to the machine vision systems to identify objects in the image.