Automated Mitotic Nuclei Classification Using Fruitfly Optimization Algorithm with Machine Learning on Breast Cancer Diagnosis
I. Gethzi Ahila Poornima, Abdul Wasim Abdul Habib Sheikh, Aruna Thota, Golagani Lavanya Devi, Neha Pandey, Sudipta Singha Roy · 2024
Mitotic nuclei classification plays an essential part in breast cancer analysis which provides an automatic and extremely exact technique to identify and classify mitotic figures in histopathological images. Mitotic figures are serious signs of cell propagation and a main norm in cancer classifying that makes their exact classification vital for defining severity and prediction of breast cancer. Leveraging advanced machine learning (ML) and computer vision models helps pathologists and oncologists by giving a trustworthy and effective device for mitotic nuclei recognition and classification. By importing speed and exactness of breast cancer diagnosis, it donates to initial involvement and personalized treatment plans, evenly enhancing patient results and complete efficacy of breast cancer management. This study presents an Automated Mitotic Nuclei Classification using Fruitfly Optimization Algorithm by Machine Learning (AMNC-FFOAML) technique on Breast Cancer Diagnosis. The AMNC-FFOAML technique concentrates on automatic detection of the mitotic nuclei within histopathological images, the AMN C-FFOAML model applies a comprehensive methodology. It starts with bilateral filtering (BF) to eradicate the noise, assuring the quality of the images. In addition, the DenseNet model is used for capturing the complex features of the images. At last, classification is performed by 1-dimensional Convolutional Autoencoders (CAE) to precisely categorize mitotic nuclei. Furthermore, the model harnesses the FFO algorithm for hyperparameter tuning, optimizing its performance. The experimental results of the AMNC-FFOAML techniques were examined on a medical image dataset. The investigational values portray a considerable development of the AMNC-FFOAML technique in detection and classification of mitotic nuclei.