Paper
1 May 1994 Scatter and veiling glare corrections for quantitative digital subtraction angiography
Atila Ersahin, Sabee Y. Molloi, Yao-Jin Qian
Author Affiliations +
Abstract
In order to quantitate anatomical and physiological parameters such as vessel dimensions and volumetric blood flow, it is necessary to make corrections for scatter and veiling glare (SVG), which are the major sources of nonlinearities in videodensitometric digital subtraction angiography (DSA). A convolution filtering technique has been investigated to estimate SVG distribution in DSA images without the need to sample the SVG for each patient. This technique utilizes exposure parameters and image gray levels to estimate SVG intensity by predicting the total thickness for every pixel in the image. At this point, corrections were also made for variation of SVG fraction with beam energy and field size. To test its ability to estimate SVG intensity, the correction technique was applied to images of a Lucite step phantom, anthropomorphic chest phantom, head phantom, and animal models at different thicknesses, projections, and beam energies. The root-mean-square (rms) percentage error of these estimates were obtained by comparison with direct SVG measurements made behind a lead strip. The average rms percentage errors in the SVG estimate for the 25 phantom studies and for the 17 animal studies were 6.22% and 7.96%, respectively. These results indicate that the SVG intensity can be estimated for a wide range of thicknesses, projections, and beam energies.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Atila Ersahin, Sabee Y. Molloi, and Yao-Jin Qian "Scatter and veiling glare corrections for quantitative digital subtraction angiography", Proc. SPIE 2163, Medical Imaging 1994: Physics of Medical Imaging, (1 May 1994); https://doi.org/10.1117/12.174253
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Cited by 7 scholarly publications.
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KEYWORDS
X-rays

Lead

Convolution

Animal model studies

Point spread functions

Signal detection

Error analysis

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