Navigating Noise and Texture: Motion Compensation Methodology for Fluorescence Lifetime Imaging in Pulmonary Research

Area of Science:

• Biomedical Optics
• Medical Imaging Technology
• In Vivo Imaging

Background:

• Real-time Fluorescence Lifetime Imaging-Optical Endomicroscopy (FLIm-OEM) faces challenges with motion artifacts in in vivo studies.
• Existing registration methods struggle with temporal motion artifacts, impacting image quality and analysis reliability.

Purpose of the Study:

• To introduce a comprehensive framework for enhanced FLIm processing in in vivo studies.
• To improve image quality by reducing motion artifacts using a novel registration technique.

Main Methods:

• Developed a framework incorporating frame discarding and a novel registration technique.
• Integrated Normalised Cross Correlation (NCC) and Channel and Spatial Reliability Tracker (CSRT) for robust motion tracking.
• Overcame optimization issues in similarity-based registration.

Main Results:

• Demonstrated significant improvement over existing methods in handling temporal FLIm motion artifacts.
• Achieved a 17% enhancement in the Quality of Alignment (QA) metric.
• Showcased a 25% increase in Structural Similarity Index Measure (SSIM) across diverse datasets.

Conclusions:

• The novel registration method significantly enhances the precision and reliability of FLIm imaging.
• This advancement is crucial for translational clinical research, particularly in pulmonary medicine.
• The framework supports the development of more effective diagnostics and treatments through improved real-time imaging.