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Proceedings Paper

A sinogram inpainting method based on generative adversarial network for limited-angle computed tomography
Author(s): Ziheng Li; Wenkun Zhang; Linyuan Wang; Ailong Cai; Ningning Liang; Bin Yan; Lei Li
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Paper Abstract

Limited-angle computed tomography (CT) image reconstruction is a challenging reconstruction problem in the fields of CT. With the development of deep learning, the generative adversarial network (GAN) perform well in image restoration by approximating the distribution of training sample data. In this paper, we proposed an effective GAN-based inpainting method to restore the missing sinogram data for limited-angle scanning. To estimate the missing data, we design the generator and discriminator of the patch-GAN and train the network to learn the data distribution of the sinogram. We obtain the reconstructed image from the restored sinogram by filtered back projection and simultaneous algebraic reconstruction technique with total variation. Experimental results show that serious artifacts caused by missing projection data can be reduced by the proposed method, and it is hopeful to solve the reconstruction problem of 60° limited scanning angle.

Paper Details

Date Published: 28 May 2019
PDF: 5 pages
Proc. SPIE 11072, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 1107220 (28 May 2019);
Show Author Affiliations
Ziheng Li, National Digital Switching System Engineering & Technological Research Ctr. (China)
Wenkun Zhang, National Digital Switching System Engineering & Technological Research Ctr. (China)
Linyuan Wang, National Digital Switching System Engineering & Technological Research Ctr. (China)
Ailong Cai, National Digital Switching System Engineering & Technological Research Ctr. (China)
Ningning Liang, National Digital Switching System Engineering & Technological Research Ctr. (China)
Bin Yan, National Digital Switching System Engineering & Technological Research Ctr. (China)
Lei Li, National Digital Switching System Engineering & Technological Research Ctr. (China)


Published in SPIE Proceedings Vol. 11072:
15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine
Samuel Matej; Scott D. Metzler, Editor(s)

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