Design and analysis of deep learning based architecture for segmantation and classification og breast cancer using histopathological images

Abstract

A lack of proper technology and equipment has made it difficult for medical newlineprofessionals and the healthcare industry to diagnose health-related issues during the past newlinefew decades. These days, computer science innovations like Internet of Things (IoT), newlineArtificial Intelligence (AI), cloud computing, and related technology are being used more newlineand more for the diagnosis, identification, and treatment of medical diseases, particularly newlinein oncology. newlineIt Machine Learning (ML) plays a crucial role in the early detection of Breast Cancer. newlineanalyses mammographic and histopathological images, assesses individual risk factors, newlinepersonalizes treatment plans based on genomic data, and provides decision support for newlinehealthcare professionals. ML contributes to post-treatment monitoring, integrates diverse newlinedatasets for comprehensive insights, and accelerates research and drug discovery efforts. newlineIt synthesizes findings from various research efforts employing diverse methodologies, newlineincluding deep learning, ensemble techniques, and innovative model architectures. newlineResearchers have explored the application of artificial neural networks, convolutional newlineneural networks, and transfer learning in increasing the accuracy and objectivity of breast newlinecancer classification. The prognosis for cancer depends on factors like the stage and type. newline120 different types of cancers can affect both men and women. A few cancers that newlineprimarily affect men are skin, lung, prostate, and colorectal. Similarly, cancer types like newlinecolorectal, ovarian, lung, breast, cervical, skin, and endometrial are most common and newlineaffect women. Breast Cancer (BC) is the second leading cause of death around the globe newlinein women. It affects primarily women of age more than 50. IARC (International Agency newlinefor Research on Cancer) reported that women die from different causes, whereas 25.2% newlinefrom BC and 9.2%, 8.7%, 7.9%, and 4.8% from colorectal, lung, cervix, and stomach newlinecancers. However, BC can also occur in men but is less common. BC forms in the cells newline