Open Access Paper
17 October 2022 Cone-beam x-ray luminescence computed tomography reconstruction based on Huber Markov Random Field regularization
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Proceedings Volume 12304, 7th International Conference on Image Formation in X-Ray Computed Tomography; 123041G (2022) https://doi.org/10.1117/12.2646587
Event: Seventh International Conference on Image Formation in X-Ray Computed Tomography (ICIFXCT 2022), 2022, Baltimore, United States
Abstract
In recent years, cone-beam X-ray luminescence computed tomography (CB-XLCT) has drawn much attention with the development of X-ray excited nanophosphors. Compared with traditional bio-optical imaging modalities such as bioluminescence tomography (BLT) and fluorescence molecular tomography (FMT), CB-XLCT can effectively improve imaging sensitivity and depth because of the reduction of background fluorescence and the high penetrability of X-rays. However, due to high degree of scattering of light through biological tissues, the reconstruction of CB-XLCT is inherently ill-conditioned. To solve the ill-posed inverse problem, appropriate priors or regularizations are needed to facilitate the reconstruction. Based on the fact that adjacent pixels generally have the same or similar concentration and in order to further balance the degree of regional smoothness and edge sharpening, a prior information model based on Huber Markov Random Field (HuMRF) was established to constrain the reconstruction process of CB-XLCT. Mice experiments indicate that compared with the traditional ART and ADAPTIK method, the proposed method could improve the image quality of CB-XLCT significantly in terms of target shape, localization accuracy and image contrast.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tianshuai Liu, Junyan Rong, Wenqin Hao, and Hongbing Lu "Cone-beam x-ray luminescence computed tomography reconstruction based on Huber Markov Random Field regularization", Proc. SPIE 12304, 7th International Conference on Image Formation in X-Ray Computed Tomography, 123041G (17 October 2022); https://doi.org/10.1117/12.2646587
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KEYWORDS
Reconstruction algorithms

Luminescence

Image quality

X-rays

X-ray imaging

Cameras

Electron multiplying charge coupled devices

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