Development of limited-angle iterative reconstruction algorithms with context encoder-based sinogram completion for micro-CT applications

Shih Chun Jin, Chia Jui Hsieh, Jyh Cheng Chen*, Shih Huan Tu, Ya Chen Chen, Tzu Chien Hsiao, Angela Liu, Wen Hsiang Chou, Woei Chyn Chu, Chih Wei Kuo

*此作品的通信作者

研究成果: Article同行評審

7 引文 斯高帕斯(Scopus)

摘要

Limited-angle iterative reconstruction (LAIR) reduces the radiation dose required for computed tomography (CT) imaging by decreasing the range of the projection angle. We developed an image-quality-based stopping-criteria method with a flexible and innovative instrument design that, when combined with LAIR, provides the image quality of a conventional CT system. This study describes the construction of different scan acquisition protocols for micro-CT system applications. Fully-sampled Feldkamp (FDK)-reconstructed images were used as references for comparison to assess the image quality produced by these tested protocols. The insufficient portions of a sinogram were inpainted by applying a context encoder (CE), a type of generative adversarial network, to the LAIR process. The context image was passed through an encoder to identify features that were connected to the decoder using a channel-wise fully-connected layer. Our results evidence the excellent performance of this novel approach. Even when we reduce the radiation dose by 1/4, the iterative-based LAIR improved the full-width half-maximum, contrast-to-noise and signal-to-noise ratios by 20% to 40% compared to a fully-sampled FDK-based reconstruction. Our data support that this CE-based sinogram completion method enhances the efficacy and efficiency of LAIR and that would allow feasibility of limited angle reconstruction.

原文English
文章編號4458
期刊Sensors (Switzerland)
18
發行號12
DOIs
出版狀態Published - 1 12月 2018

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