A Hybrid Quantum Neural Network - Assisted Deep Learning Framework for Automated Centralserous Retinopathy Detection Using Oct Images
This paper presents HQNNDL, a hybrid quantum-classical deep learning framework utilizing a frozen ResNet-18 backbone and an 8-qubit variational quantum circuit to classify OCT images into four categories, achieving 79.0% accuracy on a proxy dataset derived from Kermany OCT2017 while acknowledging the need for further ablation studies and clinical validation to confirm its efficacy for Central Serous Retinopathy detection.