&lt;title&gt;High-performance amorphous silicon image sensor for x-ray diagnostic medical imaging applications&lt;/title&gt;

Weisfield, Richard L.; Hartney, Mark A.; Schneider, R.; Aflatooni, K.; Lujan, R.

doi:10.1117/12.349505

Cited by 21 publications

(17 citation statements)

References 1 publication

(1 reference statement)

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“…They include (1) active area, (2) pixel size, (3) image acquisition rate, (4) dynamic range, as well as (5) outer dimensions and (6) weight. All of these parameters need to be selected carefully in accordance with the intended application of the detector.…”

Section: Technology and Design Of Flat Detectorsmentioning

confidence: 99%

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Flat detectors and their clinical applications

Spahn

2005

Eur Radiol

111

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Diagnostic and interventional flat detector X-ray systems are penetrating the market in all application segments. First introduced in radiography and mammography, they have conquered cardiac and general angiography and are getting increasing attention in fluoroscopy. Two flat detector technologies prevail. The dominating method is based on an indirect X-ray conversion process, using cesium iodide scintillators. It offers considerable advantages in radiography, angiography and fluoroscopy. The other method employs a direct converter such as selenium which is particularly suitable for mammography. Both flat detector technologies are based on amorphous silicon active pixel matrices. Flat detectors facilitate the clinical workflow in radiographic rooms, foster improved image quality and provide the potential to reduce dose. This added value is based on their large dynamic range, their high sensitivity to X-rays and the instant availability of the image. Advanced image processing is instrumental in these improvements and expand the range of conventional diagnostic methods. In angiography and fluoroscopy the transition from image intensifiers to flat detectors is facilitated by ample advantages they offer, such as distortion-free images, excellent coarse contrast, large dynamic range and high X-ray sensitivity. These characteristics and their compatibility with strong magnetic fields are the basis for improved diagnostic methods and innovative interventional applications.

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Section: Technology and Design Of Flat Detectorsmentioning

confidence: 99%

“…Changes of this nature are also taking place in general angiography and in fluoroscopy. Hence, flat detectors put us for the first time in a position to finally realize the vision of obtaining a single technology that covers all applications in X-ray diagnostics and interventional techniques [1][2][3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Flat detectors and their clinical applications

Spahn

2005

Eur Radiol

111

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“…Several technologies have been implemented in recent years, as photostimulable phosphors, image intensifier based detectors, charge-coupled devices (CCD), and, most recently, flat panel detectors (with amorphous selenium and silicon-based technology) [2], [3]. The amorphous silicon technology is one of the most promising [4]- [8] (resistant to radiations, high image quality, fast readout, compact size). In this paper, the technology used is first presented.…”

Section: Introductionmentioning

confidence: 99%

Real-time flat-panel pixel imaging system and control for X-ray and neutron detection

Chapuy

Dimcovski

et al. 2001

IEEE Trans. Nucl. Sci.

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We present in this paper industrial nondestructive X-ray and neutron testing applications with a real-time digital imaging device and control system X-View based on active matrix flat-panel imager technology. X-View consists of X-ray or neutron converters, arrays of amorphous silicon (a-Si:H) thin-film transistors and photodiodes, a fast real-time electronic system for readout and digitization of images and appropriate computer tools for control, real-time image treatment data representation, and off-line analysis. Some basic image-quality parameters and different objects were assessed for quantitative and qualitative analysis. Results show a wide dynamic range (16 bits ADC resolution) and lack of blooming, a high frame rate (up to 25 fps), and rapid image capture. Images are directly displayed, on-line, on a PC monitor and archived in a digital form for radiography and radioscopy procedures and limitless industrial applications in X-ray and neutron inspections.

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“…(1). When the exposure intensity on the FP changes, the lag rates and lag coefficients can change, creating a new IRF.…”

Section: Iib Nlcsc Lag Algorithmmentioning

confidence: 99%

“…For these methods, a suitable model of the lag decay is fit to the a-Si FP detector data with a multiexponential 12 signal or a power function. 1 Typically, the a-Si FP is modeled as a linear time-invariant (LTI) system, which is described by an impulse response function (IRF). The correction is a temporal deconvolution of the detector output with the modeled IRF.…”

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confidence: 99%

A nonlinear lag correction algorithm for a‐Si flat‐panel x‐ray detectors

et al. 2012

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Purpose: Detector lag, or residual signal, in a-Si flat-panel (FP) detectors can cause significant shading artifacts in cone-beam computed tomography reconstructions. To date, most correction models have assumed a linear, time-invariant (LTI) model and correct lag by deconvolution with an impulse response function (IRF). However, the lag correction is sensitive to both the exposure intensity and the technique used for determining the IRF. Even when the LTI correction that produces the minimum error is found, residual artifact remains. A new non-LTI method was developed to take into account the IRF measurement technique and exposure dependencies. Methods: First, a multiexponential (N = 4) LTI model was implemented for lag correction. Next, a non-LTI lag correction, known as the nonlinear consistent stored charge (NLCSC) method, was developed based on the LTI multiexponential method. It differs from other nonlinear lag correction algorithms in that it maintains a consistent estimate of the amount of charge stored in the FP and it does not require intimate knowledge of the semiconductor parameters specific to the FP. For the NLCSC method, all coefficients of the IRF are functions of exposure intensity. Another nonlinear lag correction method that only used an intensity weighting of the IRF was also compared. The correction algorithms were applied to step-response projection data and CT acquisitions of a large pelvic phantom and an acrylic head phantom. The authors collected rising and falling edge stepresponse data on a Varian 4030CB a-Si FP detector operating in dynamic gain mode at 15 fps at nine incident exposures (2.0%-92% of the detector saturation exposure). For projection data, 1st and 50th frame lag were measured before and after correction. For the CT reconstructions, five pairs of ROIs were defined and the maximum and mean signal differences within a pair were calculated for the different exposures and step-response edge techniques. Results: The LTI corrections left residual 1st and 50th frame lag up to 1.4% and 0.48%, while the NLCSC lag correction reduced 1st and 50th frame residual lags to less than 0.29% and 0.0052%. For CT reconstructions, the NLCSC lag correction gave an average error of 11 HU for the pelvic phantom and 3 HU for the head phantom, compared to 14-19 HU and 2-11 HU for the LTI corrections and 15 HU and 9 HU for the intensity weighted non-LTI algorithm. The maximum ROI error was always smallest for the NLCSC correction. The NLCSC correction was also superior to the intensity weighting algorithm. Conclusions: The NLCSC lag algorithm corrected for the exposure dependence of lag, provided superior image improvement for the pelvic phantom reconstruction, and gave similar results to the best case LTI results for the head phantom. The blurred ring artifact that is left over in the LTI corrections was better removed by the NLCSC correction in all cases.

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<title>High-performance amorphous silicon image sensor for x-ray diagnostic medical imaging applications</title>

Cited by 21 publications

References 1 publication

Flat detectors and their clinical applications

Flat detectors and their clinical applications

Real-time flat-panel pixel imaging system and control for X-ray and neutron detection

A nonlinear lag correction algorithm for a‐Si flat‐panel x‐ray detectors

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