Research Projects

This project aims to develop medical image processing by integrating Quantum Image Processing (QIP) with Fractal-Fractional Differentiation (FFD) to create an advanced framework for early melanoma detection. Skin cancer, particularly melanoma, remains a significant global health challenge, with early detection drastically improving survival rates. However, existing diagnostic methods face limitations when processing complex medical images with irregular lesion boundaries, noise, and low contrast. These challenges are amplified in resource-constrained settings, where real-time analysis using traditional techniques is often infeasible due to their lack of flexibility and computational efficiency. The proposed research introduces a quantum-enhanced image processing framework to address these gaps, aiming to improve segmentation accuracy for skin cancer datasets. At its core is the development of an FFD Operator (FFDO), which combines fractional calculus and fractal geometry to enable dynamic edge detection and image enhancement. By adapting fractional orders and fractal dimensions, the FFDO can accurately analyze irregular lesion structures, overcoming the shortcomings of classical edge detection methods. QIP will be utilized to encode medical images as quantum states. Quantum convolutional kernels will process these states in parallel to enhance computational efficiency and segmentation precision. This integration is expected to achieve superior performance, enabling real-time processing of large-scale, high-resolution medical datasets. Key experiments include designing and testing the FFDO for adaptive edge detection, implementing quantum convolutional kernels, and benchmarking the framework against classical methods using standard skin lesion datasets. Performance metrics such as segmentation accuracy, computational speed, and robustness to noise will be evaluated. The project aims to significantly improve early-stage melanoma detection by addressing limitations in current diagnostic tools, potentially reducing mortality rates and healthcare costs through early intervention. Beyond dermatology, the framework could benefit other fields such as neurology and cardiology, contributing to the broader advancement of quantum-enhanced medical imaging technologies. This research aligns with Sustainable Development Goals (SDG) 3 and SDG 9, promoting health and well-being while advancing innovation in medical diagnostics.