Heel effect adaptive flat field correction of digital x-ray detectors

Anode heel effect renders large-scale background nonuniformities in digital radiographs. Conventional offset/gain calibration is performed at mono source-to-image distance (SID), and disregards the SID-dependent characteristic of heel effect. It results in a residual nonuniform background in the corrected radiographs when the SID settings for calibration and correction differ. In this work, the authors develop a robust and efficient computational method for digital x-ray detector gain correction adapted to SID-variant heel effect, without resorting to physical filters, phantoms, complicated heel effect models, or multiple-SID calibration and interpolation.

The authors present the Duo-SID projection correction method. In our approach, conventional offset/gain calibrations are performed only twice, at the minimum and maximum SIDs of the system in typical clinical use. A fast iterative separation algorithm is devised to extract the detector gain and basis heel patterns from the min/max SID calibrations. The resultant detector gain is independent of SID, while the basis heel patterns are parameterized by the min- and max-SID. The heel pattern at any SID is obtained from the min-SID basis heel pattern via projection imaging principles. The system gain desired at a specific acquisition SID is then constructed using the projected heel pattern and detector gain map.

The method was evaluated for flat field and anatomical phantom image corrections. It demonstrated promising improvements over interpolation and conventional gain calibration/correction methods, lowering their correction errors by approximately 70% and 80%, respectively. The separation algorithm was able to extract the detector gain and heel patterns with less than 2% error, and the Duo-SID corrected images showed perceptually appealing uniform background across the detector.

The Duo-SID correction method has substantially improved on conventional offset/gain corrections for digital x-ray imaging in an SID-variant environment. The technique is relatively simple, and can be easily incorporated into multiple-point gain calibration/correction techniques. It offers a potentially valuable tool for preprocessing digital x-ray images to boost image quality of mammography, chest and cardiac radiography, as well as automated computer aided diagnostic radiology.