Synergistic Image Data Generation System for Hollow Organs

A novel system that integrates computed tomography scanning, AI-based material separation, blockchain-based data storage, IoT-enabled injectors and display systems, and novel nano-material-based injectors to provide enhanced image data of hollow organs, enabling accurate diagnosis and treatment.

The original patent discloses a method for providing image data of a hollow organ using computed tomography scanning and contrast agents. However, this method has limitations in terms of image resolution, material separation, and data security. The new inventive concept addresses these limitations by synergistically combining distinct technologies to provide a more powerful system for generating image data of hollow organs.

The system comprises a computed tomography scanner configured to apply a first contrast agent and a second contrast agent to the hollow organ. An AI-based material separation algorithm is used to separate the first contrast agent from the second contrast agent in the image data. The separated image data is then securely stored in a blockchain-based data storage system. Additionally, IoT-enabled injectors and display systems can be used to apply the contrast agents and display the separated image data in real-time. Furthermore, novel nano-material-based injectors can be used to apply the contrast agents. The system can analyze the image data using machine learning algorithms to identify abnormalities in the hollow organ.

The new inventive concept is novel and non-obvious compared to the original patent as it integrates distinct technologies such as AI, blockchain, IoT, and novel nano-materials to provide a more powerful system for generating image data of hollow organs. The synergistic combination of these technologies provides an inventive step over the original patent.

Alternative embodiments of the inventive concept could include using different types of contrast agents, varying the configuration of the computed tomography scanner, or using different machine learning algorithms for image analysis. Variations of the system could include using different blockchain-based data storage systems or IoT-enabled devices.

The inventive concept has significant commercial potential in the medical imaging industry, particularly in the diagnosis and treatment of hollow organ-related diseases. The system's ability to provide enhanced image data and accurate diagnosis could lead to improved patient outcomes and reduced healthcare costs.