Development of a selenium-based flat-panel detector for real-time radiography and fluoroscopy

Tsukamoto, Akira; Yamada, Shinichi; Tomisaki, Takayuki; Tanaka, Manabu; Sakaguchi, Takuya; Asahina, Hiroshi; Nishiki, Masayuki

doi:10.1117/12.317039

Cited by 30 publications

(22 citation statements)

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“…Gm_0(r)= M/S(r) (2)(3)(4)(5)(6)(7)(8)(9)(10)(11) Gm_O normalizes a calibration image S(r) to its mean value M calculated within a region of interest, and is only suitable for uniformly exposed images. As observed experimentally, however, artifacts may be introduced into reconstructed images due to non-uniform x-ray exposure in S(r).…”

Section: Gain Calibrationmentioning

confidence: 99%

“…In this implementation, the real-time background image is simply created by averaging two background images. B(r, t)=(Refj(r, t)+ Ref_2(r, t))12 (2)(3)(4)(5)(6)(7)(8) Where Ref_1(r, t) is acquired before exposure image, and Ref_2(r, t) after exposure image.…”

Section: Real-time Background Correctionmentioning

confidence: 99%

“…During the past few years new ideas have been proposed and examined for applying this new technology. While most reported works concern digital radiography and digital fluoroscopy [5][6][7][8][9][10][11][12], however, one paper was presented by our research group [13], describing an STFT array-based VTA imaging system.…”

Section: Introductionmentioning

confidence: 95%

“…First, the gain correction will be done to remove the stationary noise pattern due to non-uniform pixel response from a background-corrected image. Multiplying S(r) with a proper value of a predefined gain map will create a gain-corrected image: C(r)=S(r)xGm(r, mR, kVp) (2)(3)(4)(5)(6)(7)(8)(9) Where Gm(r, mR, kVp) represents available gain-correction factor values for the pixel at position r. For a given x-ray energy kVp, the gain value of a pixel is determined by exposure mR, which can be estimated from the mean of signal.…”

Section: Stationary Noise Pattern Correctionmentioning

confidence: 99%

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

Zhang

Ning

Chen

et al. 1999

Medical Imaging 1999: Physics of Medical Imaging

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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" x 17" STFT detector with a 2560 x 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.

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Section: Gain Calibrationmentioning

confidence: 99%

Section: Real-time Background Correctionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 95%

Section: Stationary Noise Pattern Correctionmentioning

confidence: 99%

See 2 more Smart Citations

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

Zhang

Ning

Chen

et al. 1999

Medical Imaging 1999: Physics of Medical Imaging

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show abstract

“…This widely perceived need has, in turn, stimulated considerable innovation resulting in a remarkable variety of [3] 450 256x240 61440 11.5x10.8 124 [4] 450 512x560 286720 23.0x25.2 580 [5] 450 512x560 286720 23.0x25.2(x4) 2318 [6] 270 64x40 2560 1.7x1.1 1.9 [2] 200 192x192 36864 3.8x3. 8 14.4 [7] 200 1024x1024 1048576 20x20 400 [8] 127 1536x1920 2929920 19.5x24.4 476 [9] 127 1536x1920 2929920 19.5x24.4 476 [10] 127 1536x1920 2929920 19 [13] 100 notavailable n.a.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 1998

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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.

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Progress in Lead OxideX‐Ray Photoconductive Layers

Grynko

Reznik

2022

Photoconductivity and Photoconductive Materials

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Development of a selenium-based flat-panel detector for real-time radiography and fluoroscopy

Cited by 30 publications

References 0 publications

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

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

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

Progress in Lead OxideX‐Ray Photoconductive Layers

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