학술논문

A Review - Breast Cancer Detection using Deep Learning Methods
Document Type
Conference
Source
2022 6th International Conference on Electronics, Communication and Aerospace Technology Electronics, Communication and Aerospace Technology (ICECA), 2022 6th International Conference on. :569-574 Dec, 2022
Subject
Aerospace
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Robotics and Control Systems
Deep learning
Aerospace electronics
Breast cancer
Classification algorithms
Convolutional neural networks
Prognostics and health management
Palpation
Contralateral breast
Prone position
Supine position
Histopathology
Malignant
Carcinoma in situ
Mammography
Hand held device
Ultra sonography
Invasive device
Language
Abstract
Early detection of cancer not only helps out in reducing the risk factor but also makes the treatment to be less expensive. But most of us are exposed to only limited number of techniques that are available for the prognosis of breast cancer. Mostly, considering the effects on exposure to radiations, invasive painful and expensive techniques, people often refrain from the sets of common screenings. Considering the same, the effect on the lists of existing breast cancer detection techniques and its functionalities were presented over to this paper to increase the exposure of people and gain their confidence on the same in early detection of breast cancer. Among all deep learning algorithm CNN classifier is suitable for early breast cancer detection its achieve 99% accuracy compare than other classifier.