Selenium flat-panel detector-based volume tomographic angiography imaging: phantom studies

Ning, Ruola; Lee, Denny L. Y.; Wang, Xiaohui; Zhang, Ying; Conover, David L.; Williams, Cornell L.

doi:10.1117/12.317031

Cited by 23 publications

(18 citation statements)

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“…The reader may refer to [19] for a detailed mathematical treatment of the preprocessing methods. See equations (5)- (7), shown at the bottom of the page. It also needs to be pointed that these two methods are object-dependent.…”

Section: Methods To Determine the Angular Incrementmentioning

confidence: 99%

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Methods Determining the Angular Increment of A Continuous Scan Cone-Beam CT System

Jiang

et al. 2010

IEEE Trans. Nucl. Sci.

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X-ray cone-beam computed tomography (CBCT) imaging based on the single circular orbit scan mode has become more and more popular because of its high imaging speed. Generally the X-ray source and detectors are stationary and the scanned object rotates step by step over 360 in this kind of system. In order to improve the imaging efficiency, the step rotation is sometimes replaced by the continuous rotation. For this continuous rotation, if there is an error about the number of projection images over 360 caused by the uncertainty of synchronization between the detector and the mechanical sub-system, the angular increment for the CT reconstruction may not be known exactly. The error will lead to serious artifacts in the CT images. This paper describes two possible methods determining the angular increment. Both of them are based on the statistical similarity among the projection images. They determined the angular increment by calculating the correlation coefficients and the standard deviation of the difference image between the image at 0 and the images at other angular positions. These two methods can verify each other. We performed numerical studies and experiments to demonstrate and validate the proposed approaches. Results in these studies and experiments confirm that the proposed two methods can determine the right projection number and the angular increment. The proposed approaches may find applications in CBCT system with continuous single circular orbit scan mode.

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Section: Methods To Determine the Angular Incrementmentioning

confidence: 99%

“…They are determined by averaging some frames. In (7), the new output image II and the old output image II represent two projections under two adjacent angular positions.…”

Section: Methods To Determine the Angular Incrementmentioning

confidence: 99%

Methods Determining the Angular Increment of A Continuous Scan Cone-Beam CT System

Jiang

et al. 2010

IEEE Trans. Nucl. Sci.

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“…To calculate K(s) for each pixel, we assume VB to be a constant, and fit Vj(s) to a curve within the calibration ADU range (2700 s then extend the curve for s < 2700 and s >4700 to cover the 14-bit ADU range as shown in Figure 2 (2-16) For each pixel not in bad pixel map, we estimate the signal value by s=N(r) and calculate R(r) according to (2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13), then R(r) will be checked against a given gain variation limit and the threshold for maximum allowable gain variation. As shown in Figure 2-2, there are three threshold-ranges: hi ( 1-E, i+E), h2 ( < 1-E-t4) and h3 ( > 1++t5 ) , where t4 and t5 are two gaps between these three threshold-ranges.…”

Section: Bad Pixel Mapmentioning

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: 97%

<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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“…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]). The second group of results asserts that reconstruction from such data is theoretically possible, but known reconstruction algorithms use extrapolation in the Fourier domain and are, therefore, severely ill-posed (see [7], Theorems 3.14 and 4.9, [19,17,Section 9.2]).…”

Section: Introductionmentioning

confidence: 99%

On quasi-local inversion of spiral CT data

Katsevich¹

2000

Math. Meth. Appl. Sci.

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Selenium flat-panel detector-based volume tomographic angiography imaging: phantom studies

Cited by 23 publications

References 0 publications

Methods Determining the Angular Increment of A Continuous Scan Cone-Beam CT System

Methods Determining the Angular Increment of A Continuous Scan Cone-Beam CT System

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

On quasi-local inversion of spiral CT data

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