Implementation of a Framelet-Based Spectral Reconstruction for Multi-Slice Spiral CT
Spectral CT utilizes spectral information of X-ray sources to reconstruct energy-resolved X-ray images and has wide medical applications. Compared with conventional energy-integrated CT scanners, however, spectral CT faces serious technical difficulties in hardware, and hence its clinical use has be...
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doaj-7d6e4febba494ce39b221d3bf666db832021-06-04T08:19:17ZengFrontiers Media S.A.Frontiers in Physics2296-424X2021-06-01910.3389/fphy.2021.682152682152Implementation of a Framelet-Based Spectral Reconstruction for Multi-Slice Spiral CTXin Li0Yanbo Zhang1Shuwei Mao2Shuwei Mao3Jiehua Zhu4Yangbo Ye5Yangbo Ye6School of Mathematics, Shandong University, Jinan, ChinaCheeloo College of Medicine, Shandong University, Jinan, ChinaCheeloo College of Medicine, Shandong University, Jinan, ChinaShandong Public Health Clinical Center, Jinan, ChinaDepartment of Mathematical Sciences, Georgia Southern University, Statesboro, GA, United StatesDepartment of Mathematics, University of Iowa, Iowa City, IA, United StatesAdvanced Medical Research Institute, Shandong University, Jinan, ChinaSpectral CT utilizes spectral information of X-ray sources to reconstruct energy-resolved X-ray images and has wide medical applications. Compared with conventional energy-integrated CT scanners, however, spectral CT faces serious technical difficulties in hardware, and hence its clinical use has been expensive and limited. The goal of this paper is to present a software solution and an implementation of a framelet-based spectral reconstruction algorithm for multi-slice spiral scanning based on a conventional energy-integrated CT hardware platform. In the present work, we implement the framelet-based spectral reconstruction algorithm using compute unified device architecture (CUDA) with bowtie filtration. The platform CUDA enables fast execution of the program, while the bowtie filter reduces radiation exposure. We also adopt an order-subset technique to accelerate the convergence. The multi-slice spiral scanning geometry with these additional features will make the framelet-based spectral reconstruction algorithm more powerful for clinical applications. The method provides spectral information from just one scan with a standard energy-integrating detector and produces color CT images, spectral curves of the attenuation coefficient at every point inside the object, and photoelectric images, which are all valuable imaging tools in cancerous diagnosis. The proposed algorithm is tested with a Catphan phantom and real patient data sets for its performance. In experiments with the Catphan 504 phantom, the synthesized color image reveals changes in the level of colors and details and the yellow color in Teflon indicates a special spectral property which is invisible in regular CT reconstruction. In experiments with clinical images, the synthesized color images provide some extra details which are helpful for clinical diagnosis, for example, details about the renal pelvis and lumbar join. The numerical studies indicate that the proposed method provides spectral image information which can reveal fine structures in clinical images and that the algorithm is efficient regarding to the computational time. Thus, the proposed algorithm has a great potential in practical application.https://www.frontiersin.org/articles/10.3389/fphy.2021.682152/fullspectral CTCUDAbowtie filtrationiterative reconstructionmulti-slice spiral CTframelet |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xin Li Yanbo Zhang Shuwei Mao Shuwei Mao Jiehua Zhu Yangbo Ye Yangbo Ye |
spellingShingle |
Xin Li Yanbo Zhang Shuwei Mao Shuwei Mao Jiehua Zhu Yangbo Ye Yangbo Ye Implementation of a Framelet-Based Spectral Reconstruction for Multi-Slice Spiral CT Frontiers in Physics spectral CT CUDA bowtie filtration iterative reconstruction multi-slice spiral CT framelet |
author_facet |
Xin Li Yanbo Zhang Shuwei Mao Shuwei Mao Jiehua Zhu Yangbo Ye Yangbo Ye |
author_sort |
Xin Li |
title |
Implementation of a Framelet-Based Spectral Reconstruction for Multi-Slice Spiral CT |
title_short |
Implementation of a Framelet-Based Spectral Reconstruction for Multi-Slice Spiral CT |
title_full |
Implementation of a Framelet-Based Spectral Reconstruction for Multi-Slice Spiral CT |
title_fullStr |
Implementation of a Framelet-Based Spectral Reconstruction for Multi-Slice Spiral CT |
title_full_unstemmed |
Implementation of a Framelet-Based Spectral Reconstruction for Multi-Slice Spiral CT |
title_sort |
implementation of a framelet-based spectral reconstruction for multi-slice spiral ct |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Physics |
issn |
2296-424X |
publishDate |
2021-06-01 |
description |
Spectral CT utilizes spectral information of X-ray sources to reconstruct energy-resolved X-ray images and has wide medical applications. Compared with conventional energy-integrated CT scanners, however, spectral CT faces serious technical difficulties in hardware, and hence its clinical use has been expensive and limited. The goal of this paper is to present a software solution and an implementation of a framelet-based spectral reconstruction algorithm for multi-slice spiral scanning based on a conventional energy-integrated CT hardware platform. In the present work, we implement the framelet-based spectral reconstruction algorithm using compute unified device architecture (CUDA) with bowtie filtration. The platform CUDA enables fast execution of the program, while the bowtie filter reduces radiation exposure. We also adopt an order-subset technique to accelerate the convergence. The multi-slice spiral scanning geometry with these additional features will make the framelet-based spectral reconstruction algorithm more powerful for clinical applications. The method provides spectral information from just one scan with a standard energy-integrating detector and produces color CT images, spectral curves of the attenuation coefficient at every point inside the object, and photoelectric images, which are all valuable imaging tools in cancerous diagnosis. The proposed algorithm is tested with a Catphan phantom and real patient data sets for its performance. In experiments with the Catphan 504 phantom, the synthesized color image reveals changes in the level of colors and details and the yellow color in Teflon indicates a special spectral property which is invisible in regular CT reconstruction. In experiments with clinical images, the synthesized color images provide some extra details which are helpful for clinical diagnosis, for example, details about the renal pelvis and lumbar join. The numerical studies indicate that the proposed method provides spectral image information which can reveal fine structures in clinical images and that the algorithm is efficient regarding to the computational time. Thus, the proposed algorithm has a great potential in practical application. |
topic |
spectral CT CUDA bowtie filtration iterative reconstruction multi-slice spiral CT framelet |
url |
https://www.frontiersin.org/articles/10.3389/fphy.2021.682152/full |
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