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A VGG16-Based Deep Learning System for Accurate Detection of Breast Cancer in Histopathology Images

Oishi Singh, Mehedi Hassan Adnan, Taohid Tabassum, Anisur Rahman

Abstract


This study presents a deep learning-based system for detecting breast cancer in histopathology images. Utilizing a VGG16-based convolutional neural network and the Breast Histopathology Images dataset from Kaggle, we developed a model that distinguishes between cancerous and non-cancerous tissue. Our system achieved 93% accuracy in cancer detection. Key features include heatmap generation for visual explanation and efficient processing of whole-slide images. The model's integration with existing laboratory workflows positions it as a valuable tool for assisting pathologists. This research contributes to the application of AI in cancer diagnosis, potentially enhancing the efficiency and accuracy of breast cancer detection. Future work will focus on clinical validation and capability expansion.

 


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References


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