Breast Cancer
Early Detection using Preprocessing and Data Enhancement Techniques
Paul Nithya and Nagappan A.
Res. J. Biotech.; Vol. 20(8); 181-186;
doi: https://doi.org/10.25303/208rjbt1810186; (2025)
Abstract
Breast cancer is the second most common cause of mortality for women. Early detection
and classification of breast cancer is a crucial initial step in its therapy. Different
screening methods like MRIs, ultrasounds, mammograms, computed tomography etc. are
used to obtain breast images. Because of its capacity to process vast volumes of
data, deep learning (DL), a branch of machine learning (ML), has demonstrated impressive
outcomes in a number of domains, most notably the biomedical sector.
However, the current deep learning-based breast categorization models have challenges
due to the absence of substantial data collection. In order to expand the quantity
of images, the proposed method uses a customized generative adversarial network
(Cust-GAN) for data augmentation. Additionally, to enhance image quality and remove
noise, employ adaptive bilateral filters with weight (ABFW) for image pre-processing.
