Respiratory motion correction with an improved demons algorithm for PET images

GAO Juan; CHAI Pei; YUN Ming-Kai; LIU Shuang-Quan; SHAN Bao-Ci; WEI Long

doi:10.1088/1674-1137/36/10/020

Chinese Physics C> 2012, Vol. 36> Issue(10) : 1025-1030 DOI: 10.1088/1674-1137/36/10/020

Respiratory motion correction with an improved demons algorithm for PET images

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Abstract：
Respiratory motion is a major factor that affects the quality of PET images of the thoracic area. The diaphragm moves about 15-20 mm due to respiratory motion, which substantially degrades the effective spatial resolution of PET. In this paper, a gated acquisition method is used to correct the motion effects. In this method, an improved demons algorithm is proposed to align the gated images. The experimental results show that the quality of PET images is significantly improved when using our improved method and the proposed method has a faster convergence rate than the original demons algorithm.

References

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GAO Juan, CHAI Pei, YUN Ming-Kai, LIU Shuang-Quan, SHAN Bao-Ci and WEI Long. Respiratory motion correction with an improved demons algorithm for PET images[J]. Chinese Physics C, 2012, 36(10): 1025-1030. doi: 10.1088/1674-1137/36/10/020

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Received: 2012-01-04
Revised: 2012-02-06

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沈阳化工大学材料科学与工程学院沈阳 110142

Respiratory motion correction with an improved demons algorithm for PET images

Corresponding author: SHAN Bao-Ci,

Received Date: 2012-01-04
Accepted Date: 2012-02-06
Available Online: 2012-10-05

Abstract: Respiratory motion is a major factor that affects the quality of PET images of the thoracic area. The diaphragm moves about 15-20 mm due to respiratory motion, which substantially degrades the effective spatial resolution of PET. In this paper, a gated acquisition method is used to correct the motion effects. In this method, an improved demons algorithm is proposed to align the gated images. The experimental results show that the quality of PET images is significantly improved when using our improved method and the proposed method has a faster convergence rate than the original demons algorithm.