Spatiotemporal filtering of digital angiographic image sequences corrupted by quantum mottle

Cheuk L. Chan; Barry J. Sullivan; Alan V. Sahakian; Aggelos K. Katsaggelos; Thomas Frohlich; Ernest Byrom

doi:10.1117/12.44297

Translator Disclaimer

1 July 1991 Spatiotemporal filtering of digital angiographic image sequences corrupted by quantum mottle

Cheuk L. Chan, Barry J. Sullivan, Alan V. Sahakian, Aggelos K. Katsaggelos, Thomas Frohlich, Ernest Byrom

Author Affiliations +

Proceedings Volume 1450, Biomedical Image Processing II; (1991) https://doi.org/10.1117/12.44297
Event: Electronic Imaging '91, 1991, San Jose, CA, United States

Abstract

A method is described for the spatio-temporal filtering of digital angiographic image sequences corrupted by simulated quantum mottle. An x-ray dosage reduction in coronary imaging studies inevitably leads to the introduction of quantum mottle --a Poisson distributed, signal dependent noise that occurs as a result of statistical fluctuations in the arrival of photons at the image intensifier tube. Although spatial filtering of individual frames in the sequence is often performed to improve image quality, this technique does not utilize valuable information from temporal correlations between images. The spatio-temporal filter here estimates motion trajectories for individual pixels and then filters along the direction of motion. This method is different from temporal filtering techniques that do not use motion compensation as the latter always blur the edges of the coronary arteries. Although the method is derived for the estimation of a single frame from two degraded frames of a sequence, it is easily generalized to multi-frame estimates. The performance of the above filter is examined using real image sequences corrupted by quantum mottle.

Citation Download Citation

Cheuk L. Chan, Barry J. Sullivan, Alan V. Sahakian, Aggelos K. Katsaggelos, Thomas Frohlich, and Ernest Byrom "Spatiotemporal filtering of digital angiographic image sequences corrupted by quantum mottle", Proc. SPIE 1450, Biomedical Image Processing II, (1 July 1991); https://doi.org/10.1117/12.44297

ACCESS THE FULL ARTICLE