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

Journal: The international journal of medical robotics + computer assisted surgery : MRCAS

PMID: 39921233

Abstract

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.

Authors

Ramkumar Muthukrishnan

Electronics and Communication Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, India.
Ashok Balasubramaniam

Electrical and Electronics Engineering, Karpagam College of Engineering, Coimbatore, India.
Vijaipriya Krishnasamy

Electronics and Communication Engineering, Sri Sai Ranganathan Engineering College, Coimbatore, India.
Sarath Kumar Ravichandran

Electronics and Communication Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, India.

Keywords

Algorithms Breast Neoplasms Convolutional Neural Networks Deep Learning Female Humans Image Processing, Computer-Assisted Mammography Neural Networks, Computer Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results

External Resources

View on PubMed Access via DOI PubMed (39921233)

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

Abstract

Authors

Keywords

External Resources

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