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Published on: November 30, 2022
Ensemble-based high-performance deep learning models for medical image retrieval in breast cancer detection
Aya E Fawzy1,2, Mohammed E Almandouh3,4, Mostafa Herajy5
1Information Technology Management Department, Faculty of Management Technology and Information Systems, Port Said University, Port Said, Egypt. aya_elsayed@himc.psu.edu.eg.
Abstract:
As digital imaging in healthcare grows quickly, dealing with vast medical image data is getting trickier. Content-Based Medical Image Retrieval (CBMIR) systems help with this, but they struggle because of the gap between simple image details and what these images mean in a clinical setting. This paper presents a new approach using deep learning for CBMIR that combines Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Explainable AI (XAI). Using the Breast Ultrasound Image (BUSI) dataset for training, this hybrid model classifies images and finds the relevant results based on predictions. It reaches a classification accuracy of 99.24% and performs well in retrieval tasks.
