Hybrid quantum computing based early detection of skin cancer

Abstract

As image processing techniques constantly grow in complexity & volume, meeting the required demand for data storage and computational power is a challenge. Using hybrid quantum-mechanical systems to encode and process image information could help overcome such challenges. We propose to implement a hybrid quantum mechanical system with 2 qubits operation for the purpose of classifying between cancerous and non-cancerous pigmented skin-lesions in the HAM10000 dataset. In view of the ever-increasing number of skin cancer deaths, such a system could have potential for the early diagnosis of the disease. Until fully scalable quantum hardware becomes available, the hybrid model could be a viable alternative to overcome the limitations of classical computing systems.

Subject Classification:

• 68U99

Keywords:

• Skin Cancer
• Cancer Detection
• PennyLane
• Quantum Image Processing
• Hybrid Quantum