Quantum-Augmented Framework for Noise Reduction and Contrast Enhancement in OCT Imaging for Early Retinal Disease Detection

Optical Coherence Tomography (OCT) utilizes retinal imaging to create ultra-fine cross-sectional pictures of the retina, assisting in the early identification of retinal disorders. OCT has limited clinical utility due to difficulties such as internal noise and low contrast which obscure important details in the retina. Image enhancement methods that have been proposed do not address these shortcomings or do not have the necessary rigour for clinical use. We present Q-OCT, an image enhancement framework based on quantum computing principles which applies quantum denoising and contrast amplification to augment OCT images. Q-OCT improves the visibility of retinal features and enhances the accuracy of early diagnosis. Comprehensive evaluation with benchmarks such as Structural Similarity Index Measure (SSIM), Peak Signal to Artifact Ratio (PSAR), noise reduction, processing time, and rate of artifacts also confirmed Q-OCT outperforms traditional methods in computational efficiency and quality. This work demonstrates advancements in the application of quantum computing to medical imaging and its impact in the field of retinal care and diagnostics.