Multi- class classification of breast cancer abnormalities using Deep Convolutional Neural Network (CNN).

ABSTRACT: The real cause of breast cancer is very challenging to determine and therefore early detection of the disease is necessary for reducing the death rate due to risks of breast cancer. Early detection of cancer boosts increasing the survival chance up to 8%. Primarily, breast images emanating from mammograms, X-Rays or MRI are analyzed by radiologists to detect abnormalities. However, even experienced radiologists face problems in identifying features like micro-calcifications, lumps and masses, leading to high false positive and high false negative. Recent advancement in image processing and deep learning create some hopes in devising more enhanced applications that can be used for the early detection of breast cancer. In this work, we have developed a Deep Convolutional Neural Network (CNN)

SUBMITTER: Heenaye-Mamode Khan M 

PROVIDER: S-EPMC8389446 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature