Data normalization method for a multi-source inverse geometry CT system

被引:1
|
作者
Baek, Jongduk [1 ]
Pelc, Norbert J. [1 ,2 ,3 ]
机构
[1] Stanford Univ, Dept Radiol, Stanford, CA 94305 USA
[2] Stanford Univ, Dept Biomed Engn, Stanford, CA 94305 USA
[3] Stanford Univ, Dept Elect Engn, Stanford, CA 94305 USA
关键词
ALG;
D O I
10.1117/12.912029
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
The multi-source inverse-geometry CT(MS-IGCT) system is composed of multiple sources and a small 2D detector array. Each source is activated sequentially and covers a small portion of the field-of-view (FOV) and a full FOV reconstruction is acquired by combining projection data from all sources. During the data acquisition, the intensity of each x-ray source could change, e.g. because of instability in the power supply, leading to artifacts in the reconstructed image. To reduce the image artifacts, we developed a data normalization algorithm for the MS-IGCT system. The projection data of each source shares an overlap region in 2D Radon space with another source. Thus, substantially same projection data can be generated from different sources at different gantry positions. Since at least one source can illuminate a reference channel and therefore its data can be easily normalized. This normalized projection data can be used to normalize the raw data of another source with which it shares an overlap region. By performing this normalization process sequentially, the intensity variations of all sources can be corrected. The proposed method was tested with Shepp-Logan phantom using 10% random source intensity fluctuations. While the reconstructed image showed image artifacts that result from uncorrected fluctuations, after applying the proposed normalization algorithm, image artifacts were removed.
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页数:6
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