Breast Cancer Detection With Optimized Machine Learning Techniques

Computer Engineering

The classification of breast cancer has been the subject of interest in the fields of healthcare and bioinformatics, because it is the second main reason of cancer-related deaths in women. Breast cancer can be analyzed using a biopsy where tissue is eliminated and studied under microscope. The identification of problem is based on the qualification and experienced of the MRI, who will attention for abnormal cells. However, if the MRI is not well-trained or experienced, this may lead to wrong diagnosis. With the recent proposition in image processing and machine learning domain, there is an interest in experiment to develop a strong pattern recognition based framework to improve the quality of diagnosis. In this work, we will use the image feature extraction approach and machine learning approach for the classification of breast cancer using MRI images into benign and malignant. Using MRI image we can preprocess this image after that apply feature extraction and classify the final result using CNN Classification techniques.

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