Multiparametric Characterisation of a Recursive Filtration Algorithm on a Commercial Angiographic Equipment

Digital fluoroscopy offers high temporal resolution but is limited by substantial noise. Recursive filtration improves the signal-to-noise ratio (SNR) by combining information across frames, though potentially at the cost of motion blur and contrast loss. This study evaluates recursive filtering performance in a commercial angiographic system, specifically where filter parameters (e.g. K-factor) are not explicitly disclosed. Fluoroscopic images were acquired using a rotating phantom with high- and low-contrast objects. Image quality was assessed using noise power spectrum (NPS), contrast-to-noise ratio (CNR), and lag analysis. Manual K-factor settings were compared with automatic configurations, and a model was developed to estimate the effective K-factor based on NPS characteristics. Higher K-factors yielded substantial noise reduction but increased lag and decreased contrast. Automatic filtering modes provided a more balanced outcome, achieving noise suppression comparable to high K-factor values while preserving contrast and minimising motion artefacts. Estimated K-factors from automatic modes varied with temporal frequency, reflecting adaptive filter behaviour. Understanding the effects of undisclosed filter settings is critical for protocol optimisation. These findings support adaptive filtering strategies tailored to clinical tasks, enhancing imaging performance and patient safety.