Detection of Breast Cancer from Histopathology image and Classifying Benign and Malignant State Using Machine learning

Computer Engineering

In today's world, cancer is a major public health concern. Breast cancer is a type of cancer that begins in the breast and spreads to the rest of the body. Breast cancer is one of the leading causes of death in women. Cancer occurs when cells become uncontrollably large. There are several types of breast cancer. The model proposed addressed both benign and malignant breast cancer. Breast cancer identification and classification using histopathology and ultrasound images are critical steps in computer-aided diagnosis systems. Researchers have demonstrated the ability to automate the initial level identification and classification of tumors over the last few decades. Breast cancer can be detected early, allowing patients to receive the appropriate treatment and improve their chances of survival. Deep learning (DL) and machine learning (ML) techniques are used to solve many medical problems. Several previous scientific studies on the categorization and identification of cancer tumors using various types of models have been published in the literature, but they have some limitations. The lack of a dataset, on the other hand, makes research difficult. Using the deep learning technique, the proposed methodology was created to aid in the automatic detection and diagnosis of breast cancer.

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