An Efficient Lightweight Multi Head Attention Gannet Convolutional Neural Network Based Mammograms Classification.

Background: This research aims to use deep learning to create automated systems for better breast cancer detection and categorisation in mammogram images, helping medical professionals overcome challenges such as time consumption, feature extraction issues and limited training models.

Methods: This research introduced a Lightweight Multihead attention Gannet Convolutional Neural Network (LMGCNN) to classify mammogram images effectively. It used wiener filtering, unsharp masking, and adaptive histogram equalisation to enhance images and remove noise, followed by Grey-Level Co-occurrence Matrix (GLCM) for feature extraction.