Scattered radiation in flat-detector based cone-beam CT: Propagation of signal, contrast and noise into reconstructed volumes

被引:0
|
作者
Wiegert, Jens [1 ]
Hohmann, Steffen [1 ]
Bertram, Matthias [1 ]
机构
[1] Philips Res Labs, Weisshausstr 2, D-52066 Aachen, Germany
关键词
cone-beam computed tomography; X-ray scatter; Monte-Carlo simulations; noise propagation; contrast-to-noise; anti-scatter grids; scatter correction;
D O I
10.1117/12.710196
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
This paper presents a novel framework for the systematic assessment of the impact of scattered radiation in flat-detector based cone-beam CT. While it is well known that scattered radiation causes three different types of artifacts in reconstructed images (inhomogeneity artifacts such as cupping and streaks, degradation of contrast, and enhancement of noise), investigations in the literature quantify the impact of scatter mostly only in terms of inhomogeneity artifacts, giving little insight, e.g., into the visibility of low contrast lesions. Therefore, for this study a novel framework has been developed that in addition to normal reconstruction of the CT (HU) number allows for reconstruction of voxelized expectation values of three additional important characteristics of image quality: signal degradation, contrast reduction, and noise variances. The new framework has been applied to projection data obtained with voxelized Monte-Carlo simulations of clinical CT data sets of high spatial resolution. Using these data, the impact of scattered radiation was thoroughly studied for realistic and clinically relevant patient geometries of the head, thorax, and pelvis region. By means of spatially resolved reconstructions of contrast and noise propagation, the image quality of a scenario with using standard antiscatter grids could be evaluated with great detail. Results show the spatially resolved contrast degradation and the spatially resolved expected standard deviation of the noise at any position in the reconstructed object. The new framework represents a general tool for analyzing image quality in reconstructed images.
引用
收藏
页数:12
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