Data normalization method for a multisource inverse geometry CT system

Jongduk Baek; Norbert J. Pelc

doi:10.1117/12.912029

3 March 2012 Data normalization method for a multisource inverse geometry CT system

Jongduk Baek, Norbert J. Pelc

Proceedings Volume 8313, Medical Imaging 2012: Physics of Medical Imaging; 83132B (2012) https://doi.org/10.1117/12.912029
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

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.

Citation Download Citation

Jongduk Baek and Norbert J. Pelc "Data normalization method for a multisource inverse geometry CT system", Proc. SPIE 8313, Medical Imaging 2012: Physics of Medical Imaging, 83132B (3 March 2012); https://doi.org/10.1117/12.912029

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