One advantage of flat-panel X-ray detectors is the immediate availability of the acquired images for display. Current limitations in large-area active-matrix manufacturing technology, however, require that the images read out from such detectors be processed to correct for inactive pixels. In static radiographs, these defects can only be interpolated by spatial filtering. Moving X-ray image modalities, such as fluoroscopy or cine-angiography, permit to use temporal information as well. This paper describes interframe defect interpolation algorithms based on motion compensation and filtering. Assuming the locations of the defects to be known, we fill in the defective areas from past frames, where the missing information was visible due to motion. The motion estimator is based on regularized block matching, with speedup obtained by successive elimination and related measures. To avoid the motion estimator locking on to static defects, these are cut out of each block during matching. Once motion is estimated, three methods are available for defect interpolation: direct filling-in by the motion-compensated predecessor, filling-in by a 3D-multilevel median filtered value, and spatiotemporal mean filtering. Results are shown for noisy fluoroscopy sequences acquired in clinical routine with varying amounts of motion and simulated defects up to six lines wide. They show that the 3D-multilevel median filter appears as the method of choice since it causes the least blur of the interpolated data, is robust with respect to motion estimation errors and works even in non-moving areas.

Date Published: 12 May 2004
PDF: 12 pages
Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004); doi: 10.1117/12.531865

Published in SPIE Proceedings Vol. 5370:
Medical Imaging 2004: Image Processing
J. Michael Fitzpatrick; Milan Sonka, Editor(s)