Paper
16 March 2011 Dose reduction using prior image constrained compressed sensing (DR-PICCS)
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Abstract
A technique for dose reduction using prior image constrained compressed sensing (DR-PICCS) in computed tomography (CT) is proposed in this work. In DR-PICCS, a standard FBP reconstructed image is forward projected to get a fully sampled projection data set. Meanwhile, it is low-pass filtered and used as the prior image in the PICCS reconstruction framework. Next, the prior image and the forward projection data are used together by the PICCS algorithm to obtain a low noise DR-PICCS reconstruction, which maintains the spatial resolution of the original FBP images. The spatial resolution of DR-PICCS was studied using a Catphan phantom by MTF measurement. The noise reduction factor, CT number change and noise texture were studied using human subject data consisting of 20 CT colonography exams performed under an IRB-approved protocol. In each human subject study, six ROIs (two soft tissue, two colonic air columns, and two subcutaneous fat) were selected for the CT number and noise measurements study. Skewness and kurtosis were used as figures of merit to indicate the noise texture. A Bland-Altman analysis was performed to study the accuracy of the CT number. The results showed that, compared with FBP reconstructions, the MTF curve shows very little change in DR-PICCS reconstructions, spatial resolution loss is less than 0.1 lp/cm, and the noise standard deviation can be reduced by a factor of 3 with DR-PICCS. The CT numbers in FBP and DR-PICCS reconstructions agree well, which indicates that DR-PICCS does not change CT numbers. The noise textures indicators measured from DR-PICCS images are in a similar range as FBP images.
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Jie Tang, Pascal Thériault Lauzier, and Guang-Hong Chen "Dose reduction using prior image constrained compressed sensing (DR-PICCS)", Proc. SPIE 7961, Medical Imaging 2011: Physics of Medical Imaging, 79612K (16 March 2011); https://doi.org/10.1117/12.878200
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Cited by 14 scholarly publications and 2 patents.
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KEYWORDS
Modulation transfer functions

Spatial resolution

Computed tomography

CT reconstruction

Reconstruction algorithms

Human subjects

Image filtering

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