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

The flat panel detector (FPD) has become a highly promising candidate for a wide variety of applications. A prototype selenium thin film transistor (STFT) array-based volume tomographic angiography (VTA) imaging system has been constructed for the feasibility study. This experimental set-up uses a 14″×17″ STFT detector with a 2560×3072 array of 14 bit pixels. While an STFT detector offers high resolution digital images, there will always be some defects on the detector. These defects will result in severe streaks and ring artifacts, which have been found in reconstructed images of preliminary phantom studies. It is obvious that the stationary noise sources of the FPD are enhanced by the reconstruction procedure. In this paper, an accurate and efficient FPD calibration method for the VTA imaging system is proposed to reduce the artifacts. An improved gain map and a bad pixel detection method with an adaptive threshold are introduced based on statistical models of the FPD. A more efficient localized and sensitive bad pixel detection ability is obtained by sub-dividing the detector array into sub-arrays, classifying bad pixels as different regional patterns, and then optimizing an interpolation scheme for each pattern. The real-time background correction, gain correction, bad-pixel correction, and methods to generate calibration maps are described in detail. The calibration technique is examined through phantom studies and evaluated by comparing the artifacts and noise in reconstructed images. Improvement of image quality is obtained utilizing the calibration technique. It has been clearly verified that the streaks and ring artifacts in reconstructed VTA images are significantly reduced. Finally, the advantages of our method and future works are also discussed.