Quantitative digital subtraction angiography: two scanning techniques for correction of scattered radiation and veiling glare. Work in progress.

Abstract

Scattered radiation and veiling glare in digital subtraction angiography degrade contrast signals in a nonlinear and nonuniform way. This effect prohibits direct use of image data for accurate iodine measurement or energy subtraction imaging. Two techniques based on the use of scanning lead bars were proposed to measure the spatial distribution of scattered radiation and veiling glare in the unprocessed image data. With either technique, signals behind the lead bars were used to estimate the scatter-glare component and remove it from the image data. The scanning-lead-bar techniques can be used to reduce the scatter-glare component by a factor of up to 10. The scatter-glare correction leads to the recovery of degraded contrast signals and achieves reasonable linearity, uniformity, and consistency in the contrast measurement.

The effect of scatter and glare on image quality in contrast‐enhanced breast imaging using an full‐field flat panel detector

“…In addition, in CE x-ray imaging, scatter and glare affect the measurement accuracy of the x-ray transmission of the iodine contrast agent, resulting in erroneous iodine concentration quantification. 7,[15][16][17][18] The effects of scatter and glare on iodine quantification are well known and have been described for dual-energy cardiac imaging and digital subtraction angiography, [15][16][17] as well as for CE breast x-ray imaging. 7,18 Within the conventional low x-ray energy range used in fullfield digital mammography ͑FFDM͒, the scatter-to-primaryratio ͑SPR͒ exiting the breast can range from approximately 0.1 to 1.3, depending on breast size and other parameters.…”

Restoration of Chest X-ray by Kalman Filter

“…Fig. 2(b) and (c), respectively are the generated imaging plate 1 and imaging plate 2 images by applying (5), (6), and (23)-(25). As long as the associated (S/N) of the imaging plate 1 and imaging plate 2 were respectively larger the 40 and 10 dBs, by using the method explained in Section III−B, we succeeded to find all unknown parameters (β; σ 1 (j), σ 2 (j), R 1 (j), and R 2 (j); j=1, 2, ••• , N) with less than 5% errors.…”

“…However, grids and air gaps can not completely eliminate the X-ray scatter reaching the detector and slit scanning systems suffer from motion artifacts and high X-ray tube loading [5]. Under such circumstances, post-processing techniques have been employed to improve the quality of the resultant X-ray image with either sampling the scatter throughout the image using radio-opaque beam-stops [6], [7], or modeling the scatter mathematically and then correcting it using digital filtering techniques [1]- [5], [7]- [13]. As it was explained in [5], the techniques that use radio-opaque beam-stop require additional exposure to directly sample the intensity of scattered radiation and can not be applied in the case of consecutive image acquisition such as cardiac imaging.…”

<title>Low-dose x-ray imaging GLG: restoration by Kalman filter</title>

“…Referring to the above statements, (3) can be expressed as follows di(x,y) = p(x,y)*h1(x,y)+ni(x,y), (5) d2(x,y) = p(x,y)*3h2(x,y)+n2(x,y). (6) In this research, our goal is to estimate p(x, y), using (I) the recorded data of the IPs (dk(x, y); k = 1, 2), (II) given Gaussian convolution-kernel with unknown parameters, and (III) given stochastic behavior of noise. In the actual X-ray images the unknown parameters of ai, cr2 , R1 , and R2 are spatially variable.…”