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

In addressing the challenges in real-time Fluorescence Lifetime Imaging (FLIm)-Optical Endomicroscopy (OEM), particularly motion artefacts, this study introduces a comprehensive framework designed to enhance FLIm processing in in vivo studies. The framework focuses on improving image quality by selectively discarding uninformative frames and employing a novel registration technique. This technique integrates Normalised Cross Correlation (NCC) and Channel and Spatial Reliability Tracker (CSRT) to consistently track the dominant correlation peak across temporal sequences of images, thus enhancing the reliability and precision of subsequent analyses. This approach has shown a significant improvement upon existing registration methods in handling temporal FLIm motion artefacts. Our method overcomes the optimisation issues inherent in similarity-based registration and demonstrates a 17% enhancement in Quality of Alignment (QA) metric and a 25% increase in Structural Similarity Index Measure (SSIM) across various datasets. Clinical relevance— Our study introduces a significant advancement in FLIm imaging, with a novel method that increases the precision and reliability of the registration. This enhancement is crucial for the translational clinical research sphere, where precise, real-time imaging underpins the development of more effective diagnostics and treatments in pulmonary medicine.