An Ensemble Deep Learning Approach for Breast Cancer Classification Using Vision Transformers and CNNs

Jose, Teny (2025) An Ensemble Deep Learning Approach for Breast Cancer Classification Using Vision Transformers and CNNs. Masters thesis, Dublin, National College of Ireland.

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Abstract

Breast cancer is still one of the most prevalent causes of cancer death globally indicating that there is a critical need for early and precise diagnostic methods. While histopathological examination remains a common method for breast cancer diagnosis, the challenge is that its accuracy and reliability depend significantly on the experience and subjective interpretations of pathologists. Deep learning techniques are increasingly being applied to classify histopathological images for breast cancer diagnosis. The proposed framework examined three state-of-the-art deep neural network architectures - Inception-v4, EfficientNet-B0, and Vision Transformer (ViT) - for the binary classification of breast histology images into benign and malignant categories. Study utilized the BreakHis dataset containing 7909 histopathological images as the training dataset, in addition, an external validation BACH dataset was used consisting of 400 images. Diagnostic performance on the external test set was further increased by an ensemble of the models. Results of stacking ensemble method significantly outperformed individual models, achieving an accuracy of 92% and ROC-AUC of 0.99 on the external BACH dataset. The results indicate that ensemble deep learning methods are clinically useful and effective as they mitigate the range of subjective diagnostic differences that exist, improving accuracy of breast cancer detection.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Sahni, Anu UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > Life sciences > Medical sciences > Pathology > Tumors > Cancer R Medicine > Healthcare Industry
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	18 Nov 2025 17:29
Last Modified:	18 Nov 2025 17:29
URI:	https://norma.ncirl.ie/id/eprint/8942

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