Large-area 97-μm pitch indirect-detection active-matrix flat-panel imager (AMFPI)

Abstract

The development of the highest resolution, large-area, active-matrix, flat-panel imager (AMFPI) thus far reported is described. This imager is based on a 97 jtm pixel pitch array with each pixel comprising a single a-Si:H TFT coupled to a discrete a-Si:H n-i-p photodiode. While the initial configuration chosen for fabrication is a 2048x2048 pixel array, a larger monolithic array format of 3072x4096 pixels is also permitted by the design. When coupled to an overlying scintillator such as a phosphor screen or CsI:Tl, the array allows indirect detection of incident radiation. The array is operated in conjunction with a recently completed electronic acquisition system featuring asynchronous operation, a large addressing range, fast analog signal extraction and digitization, and 16-bit digitization. This imager, whose empirical characterization will be reported in a subsequent paper, was developed as an engineering prototype to allow investigation of the performance limits of the most aggressive array designs permitted by present active-matrix technology. The development of this new imager builds upon knowledge acquired from the iterative design, fabrication, and quantitative evaluation of earlier engineering prototypes based on a series of 127 im pitch arrays. This paper summarizes the general program of research leading to this new device and puts this in the context of world-wide developments in indirect and direct detection AMFPI technology. Some limitations of present AMFPI technology are described, and possible solutions are discussed.Specifically, the incorporation of multiplexers based on poly-crystalline silicon circuitry into the array design, to facilitate very high resolution imagers, are proposed. In addition, strategies to significantly improve AMFPI performance at very low exposures, such as those commonly encountered in fluoroscopy, involving the reduction of additive noise (such as through lower preamplifier noise) and the enhancement of system gain (such as through the use of lead iodide) are discussed and initial calculations illustrating potential levels ofperformance are presented.

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

“…S(r)=<I(r, t)> -<B(r, t)> (2)(3)(4) k(r, t)= S(r)/Nd(r, t) (2)(3)(4)(5) Where I(r, t) is the detector output, B(r, t) is the background additive noise, S(r) is the background-corrected signal, and k(r, t) is the gain of a pixel. The non-uniformity of gain is a multiplicative noise source of the detector.…”

“…The non-uniformity of gain is a multiplicative noise source of the detector. The gain can be calculated from equation (2)(3)(4)(5), or estimated from the relation between the variance of the detector output and the number of detected photons below.…”

On quasi-local inversion of spiral CT data

“…This is due to the fact that calculation of f is more demanding than calculation of f @ . Note that known #at panel detectors can have up to 2000;2000 pixels (individual detectors) [1].…”

“…Such data are called the truncated cone beam data, because not all the X-rays that intersect the patient are detected. Note that quite a few very high-resolution 2-D detector arrays have already been developed [1], and their use in CT is being actively investigated (see, e.g. [15]).…”

“…Computation of the Radon transform data can be done only after the scan has been completed. Moreover, one would either have to keep all the cone beam data in memory (this is not always possible because for each source position one could potentially have on the order of 10 data points [1]) or read the data from the hard drive as needed (this can slow down calculations considerably). An e$cient approximate algorithm for inverting the truncated cone beam data is proposed in [14].…”