Accurate and efficient calibration method for a selenium flat-panel detector-based volume tomographic angiography imaging system

It researched correction problem of the flat panel detector (FPD) by phantom testing. A calibration method based on statistical models of the FPD is proposed. The generation of calibration matrix for bad pixels detection and a calibration method of original projection image are discussed. It includes the real-time background correction, image standardization, gain correction, and bad pixels correction. The calibration algorithm is examined through phantom studies and evaluated by comparing the artifacts and noise in reconstructed images. It is obvious that the stationary noise sources of the FPD will be enhanced in reconstructed images. These defects will result in severe streaks and ring artifacts. Improvement of image quality is obtained utilizing the calibration technique. It has been clearly verified that the streaks and ring artifacts in reconstructed images are significantly reduced.