Neural network for improved performance of medical imaging systems

US12073538B2 · kind B2 · utility

Assignee

• CANON MEDICAL SYSTEMS CORPORATION · JP

Inventors

• Chung Chan · Vernon Hills, US
• Li YANG · Vernon Hills, US
• Wenyuan Qi · Vernon Hills, US
• Evren Asma · Vernon Hills, US
• Jeffrey KOLTHAMMER · Vernon Hills, US
• Yi Qiang · San Francisco, US

Key dates

• Filing date: Apr 8, 2021
• Grant date: Aug 27, 2024
• Expiry date: Jan 20, 2042

Classification

• Technology area (CPC G): Physics
• CPC primary: G06T2211/441
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

Existing, low quality images can be restored using reconstruction or a combination of post-reconstruction techniques to generate a real patient phantom. The real patient phantom (RPP) can then be simulated in Monte Carlo simulations of a higher performance system and a lower performance system. Alternatively, the RPP can be simulated in the higher performance system, and a real scan can be performed by an existing, lower performance system. The higher performance system can be differentiated from the lower performance system in a variety of ways, including a higher resolution time of flight measurement capability, a greater sensitivity, smaller detector crystals, or less scattering. A neural network can be trained using the images produce by the higher performance system as the target, and the images produced by the lower performance system as the input. After training, the trained neural network can be used to output input images taken in a lower performance system with higher performance system characteristics.