An Adaptive Non-Local-Means Filter for Real-Time MR-Thermometry

Area of Science:

• Medical Physics
• Biomedical Engineering
• Radiology

Background:

• Proton resonance frequency shift-based MR thermometry is crucial for monitoring temperature in thermal therapies.
• Fast MR acquisition for real-time updates can introduce noise, impacting therapy control and endpoint detection.

Purpose of the Study:

• To develop an improved non-local filtering technique for MR thermometry temperature images.
• To enhance measurement precision and accuracy while maintaining real-time performance.

Main Methods:

• An improved non-local filtering technique was developed, incorporating spatial and temporal information.
• The method was optimized for real-time processing with minimal latency.
• Validation was performed using simulation, ex-vivo, and in-vivo experiments.

Main Results:

• The proposed filtering approach demonstrated significant improvements in accuracy and precision compared to existing methods.
• The technique effectively reduces noise in temperature measurements from MR thermometry.
• Validated across simulation, ex-vivo, and in-vivo studies.

Conclusions:

• The improved non-local filtering technique offers enhanced precision and accuracy for MR thermometry.
• Its real-time capability and low computational demand make it suitable for targeted thermal therapies.
• This method shows potential for improving temperature monitoring in clinical applications.