Synergistic Functional OCT Data Processing

Integrating functional OCT image data processing with distinct technologies such as AI, IoT, blockchain, and new materials to create a more powerful system for generating indications of retinal response to light stimuli.

The original patent disclosed a method for processing functional OCT image data to generate an indication of retinal response to light stimuli. However, the patent's approach was limited to a single technology and lacked the benefits of synergistic combinations. The new inventive concept addresses this limitation by integrating functional OCT data processing with other distinct technologies, enabling more accurate, secure, and efficient processing of retinal response data.

The synergistic system comprises a receiver module configured to receive OCT image data and stimulus data, a correlation calculator module utilizing AI-based correlation calculation, an IoT-enabled receiver module for receiving data from multiple OCT imaging devices, a blockchain-based storage module for secure storage of calculated correlation values, and a machine learning-based analyzer module for identifying patterns in the calculated correlation values. The system can generate 3D printed models of the retina based on the calculated correlation values and display the results in a graphical format.

The new claims introduce novel synergistic combinations of functional OCT data processing with AI, IoT, blockchain, and new materials, providing a non-obvious improvement over the original patent by enabling more accurate, secure, and efficient processing of retinal response data.

Alternative embodiments may include integrating functional OCT data processing with other technologies such as cloud computing, edge computing, or advanced materials. Variations may include adapting the system for use in different medical applications, such as processing OCT data for cancer detection or monitoring.

The synergistic functional OCT data processing system has significant commercial potential in the medical imaging and diagnostics industry, particularly in ophthalmology and optometry. The system's ability to provide more accurate and efficient processing of retinal response data can improve diagnosis and treatment of retinal diseases, leading to increased market demand and potential revenue growth.