A Convolutional Neural Network Based Patch Classifier Using Mammograms

Yumnah Hasan, Aidan Murphy, Meghana Kshirsagar, Conor Ryan

2023

Abstract

Breast Cancer is the most prevalent cancer among females worldwide. Early detection is key to good prognosis and mammography is the most widely-used technique, particularly in screening programs. However, mammography is a highly-skilled and often time-consuming task. Deep learning methods can facilitate the detection process and assist clinicians in disease diagnosis. There has been much research showing Deep Neural Networks’ successful use in medical imaging to predict early and accurate diagnosis. This paper proposes a patch-based Convolutional Neural Network (CNN) classification approach to classify patches (small sections) obtained from mammogram images into either benign or malignant cases. A novel patch extraction approach method, which we call Overlapping Patch Extraction, is developed and compared with the two different techniques, Non-Overlapping Patch Extraction, and a Region-Based-Extraction. Experimentation is conducted using images from the Curated Breast Imaging Subset of Digital Database for Screening Mammography. Five deep learning models, three configurations of EfficientNet-V2 (B0, B2, and L), ResNet-101, and MobileNetV3L, are trained on the patches extracted using the discussed methods. Preliminary results indicate that the proposed patch extraction approach, Overlapping, produces a more robust patch dataset. Promising results are obtained using the Overlapping patch extraction technique trained on the EfficientNet-V2L model achieving an AUC of 0.90.

Paper Citation

in Harvard Style

Hasan Y., Murphy A., Kshirsagar M. and Ryan C. (2023). A Convolutional Neural Network Based Patch Classifier Using Mammograms. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-623-1, pages 869-876. DOI: 10.5220/0011790800003393

in Bibtex Style

@conference{icaart23,
author={Yumnah Hasan and Aidan Murphy and Meghana Kshirsagar and Conor Ryan},
title={A Convolutional Neural Network Based Patch Classifier Using Mammograms},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2023},
pages={869-876},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011790800003393},
isbn={978-989-758-623-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
TI - A Convolutional Neural Network Based Patch Classifier Using Mammograms
SN - 978-989-758-623-1
AU - Hasan Y.
AU - Murphy A.
AU - Kshirsagar M.
AU - Ryan C.
PY - 2023
SP - 869
EP - 876
DO - 10.5220/0011790800003393