Back to Search
ReviewOpen Access

A Comprehensive Survey on Deep-Learning-Based Breast Cancer Diagnosis

Author Affiliations
Bangladesh University of Business and Technology, King Abdulaziz University, University of Asia Pacific, University of Ulsan
Published InCancers
Year2021
Citations91

Abstract

Breast cancer is now the most frequently diagnosed cancer in women, and its percentage is gradually increasing. Optimistically, there is a good chance of recovery from breast cancer if identified and treated at an early stage. Therefore, several researchers have established deep-learning-based automated methods for their efficiency and accuracy in predicting the growth of cancer cells utilizing medical imaging modalities. As of yet, few review studies on breast cancer diagnosis are available that summarize some existing studies. However, these studies were unable to address emerging architectures and modalities in breast cancer diagnosis. This review focuses on the evolving architectures of deep learning for breast cancer detection. In what follows, this survey presents existing deep-learning-based architectures, analyzes the strengths and limitations…
View at Publisher

BORR does not host full-text PDFs. The button above takes you to the original publisher.