Noise estimation in cardiac x-ray imaging: a machine vision approach

We propose a method to automatically parameterize noise in cardiac x-ray image sequences. The aim was to provide context-sensitive imaging information for use in regulating dose control feedback systems that relates to the experience of human observers. The algorithm locates and measures noise contained in areas of approximately equal signal level. A single noise metric is derived from the dominant noise components based on their magnitude and spatial location in relation to clinically relevant structures. The output of the algorithm was compared to noise and clinical acceptability ratings from 28 observers viewing 40 different cardiac x-ray imaging sequences. Results show good agreement and that the algorithm has the potential to augment existing control strategies to deliver x-ray dose to the patient on an individual basis.