Paper
12 May 2004 Motion-compensated defect interpolation for flat-panel detectors
Til Aach, Erhardt Barth, Claudia Mayntz
Author Affiliations +
Abstract
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.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Til Aach, Erhardt Barth, and Claudia Mayntz "Motion-compensated defect interpolation for flat-panel detectors", Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004); https://doi.org/10.1117/12.531865
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KEYWORDS
Motion estimation

Digital filtering

Fluoroscopy

Nonlinear filtering

Sensors

Detection and tracking algorithms

X-rays

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