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MICCAI
2010
Springer

4D Computed Tomography Reconstruction from Few-Projection Data via Temporal Non-local Regularization

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4D Computed Tomography Reconstruction from Few-Projection Data via Temporal Non-local Regularization
Abstract. 4D computed tomography (4D-CT) is an important modality in medical imaging due to its ability to resolve patient anatomy motion in each respiratory phase. Conventionally 4D-CT is accomplished by performing the reconstruction for each phase independently as in a CT reconstruction problem. We propose a new 4D-CT reconstruction algorithm that explicitly takes into account the temporal regularization in a non-local fashion. By imposing a regularization of a temporal non-local means (TNLM) form, 4D-CT images at all phases can be reconstructed simultaneously based on extremely under-sampled x-ray projections. Our algorithm is validated in one digital NCAT thorax phantom and two real patient cases. It is found that our TNLM algorithm is capable of reconstructing the 4D-CT images with great accuracy. The experiments also show that our approach outperforms standard 4D-CT reconstruction methods with spatial regularization of total variation or tight frames.
Xun Jia, Yifei Lou, Bin Dong, Zhen Tian, Steve B.
Added 29 Jan 2011
Updated 29 Jan 2011
Type Journal
Year 2010
Where MICCAI
Authors Xun Jia, Yifei Lou, Bin Dong, Zhen Tian, Steve B. Jiang
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