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A sparse-projection computed tomography reconstruction method for in vivo application of in-line phase-contrast imaging.

Wang L, Li X, Wu M, Zhang L, Luo S - Biomed Eng Online (2013)

Bottom Line: In recent years, X-ray phase-contrast imaging techniques have been extensively studied to visualize weakly absorbing objects.Combined with computed tomography (CT), phase-contrast CT can produce 3D volumetric images of samples.To date, the most common reconstruction method for phase-contrast X-ray CT imaging has been filtered back projection (FBP).

View Article: PubMed Central - HTML - PubMed

Affiliation: College of Biomedical Engineering, Capital Medical University, You An Men, Beijing 100069, People's Republic of China.

ABSTRACT

Background: In recent years, X-ray phase-contrast imaging techniques have been extensively studied to visualize weakly absorbing objects. One of the most popular methods for phase-contrast imaging is in-line phase-contrast imaging (ILPCI). Combined with computed tomography (CT), phase-contrast CT can produce 3D volumetric images of samples. To date, the most common reconstruction method for phase-contrast X-ray CT imaging has been filtered back projection (FBP). However, because of the impact of respiration, lung slices cannot be reconstructed in vivo for a mouse using this method. Methods for reducing the radiation dose and the sampling time must also be considered.

Methods: This paper proposes a novel method of in vivo mouse lung in-line phase-contrast imaging that has two primary improvements compared with recent methods: 1) using a compressed sensing (CS) theory-based CT reconstruction method for the in vivo in-line phase-contrast imaging application and 2) using the breathing phase extraction method to address the lung and rib cage movement caused by a live mouse's breathing.

Results: Experiments were performed to test the breathing phase extraction method as applied to the lung and rib cage movement of a live mouse. Results with a live mouse specimen demonstrate that our method can reconstruct images of in vivo mouse lung.

Conclusions: The results demonstrate that our method could deal with vivo mouse's breathing and movements, meanwhile, using less sampling data than FBP while maintaining the same high quality.

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Alignment results for two images at different angles, 0° and 1.
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Figure 6: Alignment results for two images at different angles, 0° and 1.

Mentions: Respiratory cycle curves can be drawn after the calculation of the two parameters. Two stages, expand to maximum and contract to minimum, are extracted. Alignment of images taken at different angles is the next step (Results shown in Figure 6). Images taken at different angles have similar covariant characteristics. In this paper, 180 images from 1° to 180° are aligned. The performance of alignment algorithm is listed in Table 1. Here we take 1° to 5° for example to illustrate the numerical results of time and number of matching points.


A sparse-projection computed tomography reconstruction method for in vivo application of in-line phase-contrast imaging.

Wang L, Li X, Wu M, Zhang L, Luo S - Biomed Eng Online (2013)

Alignment results for two images at different angles, 0° and 1.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3750831&req=5

Figure 6: Alignment results for two images at different angles, 0° and 1.
Mentions: Respiratory cycle curves can be drawn after the calculation of the two parameters. Two stages, expand to maximum and contract to minimum, are extracted. Alignment of images taken at different angles is the next step (Results shown in Figure 6). Images taken at different angles have similar covariant characteristics. In this paper, 180 images from 1° to 180° are aligned. The performance of alignment algorithm is listed in Table 1. Here we take 1° to 5° for example to illustrate the numerical results of time and number of matching points.

Bottom Line: In recent years, X-ray phase-contrast imaging techniques have been extensively studied to visualize weakly absorbing objects.Combined with computed tomography (CT), phase-contrast CT can produce 3D volumetric images of samples.To date, the most common reconstruction method for phase-contrast X-ray CT imaging has been filtered back projection (FBP).

View Article: PubMed Central - HTML - PubMed

Affiliation: College of Biomedical Engineering, Capital Medical University, You An Men, Beijing 100069, People's Republic of China.

ABSTRACT

Background: In recent years, X-ray phase-contrast imaging techniques have been extensively studied to visualize weakly absorbing objects. One of the most popular methods for phase-contrast imaging is in-line phase-contrast imaging (ILPCI). Combined with computed tomography (CT), phase-contrast CT can produce 3D volumetric images of samples. To date, the most common reconstruction method for phase-contrast X-ray CT imaging has been filtered back projection (FBP). However, because of the impact of respiration, lung slices cannot be reconstructed in vivo for a mouse using this method. Methods for reducing the radiation dose and the sampling time must also be considered.

Methods: This paper proposes a novel method of in vivo mouse lung in-line phase-contrast imaging that has two primary improvements compared with recent methods: 1) using a compressed sensing (CS) theory-based CT reconstruction method for the in vivo in-line phase-contrast imaging application and 2) using the breathing phase extraction method to address the lung and rib cage movement caused by a live mouse's breathing.

Results: Experiments were performed to test the breathing phase extraction method as applied to the lung and rib cage movement of a live mouse. Results with a live mouse specimen demonstrate that our method can reconstruct images of in vivo mouse lung.

Conclusions: The results demonstrate that our method could deal with vivo mouse's breathing and movements, meanwhile, using less sampling data than FBP while maintaining the same high quality.

Show MeSH