基于多电压x射线图像分解的窄能宽CT。

IF 3.3 Q2 ENGINEERING, BIOMEDICAL
International Journal of Biomedical Imaging Pub Date : 2017-01-01 Epub Date: 2017-11-07 DOI:10.1155/2017/8126019
Jiaotong Wei, Yan Han, Ping Chen
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引用次数: 3

摘要

多色x射线束使重建图像的灰度取决于其在固体和被成像材料中的位置。这个因素使得通过计算机断层扫描(CT)成像进行定量测量非常困难。为了获得窄能宽重构图像,我们提出了一种利用x射线散射的低频特性将多电压x射线图像分解成多个窄能宽x射线图像的模型。在典型的CT系统中不需要改变硬件。对分解模型进行求解,得到窄能量宽度投影,用于图像重构。在验证实验中,采用了由铝和硅组成的圆筒。部分重构图像可以看作是真实的窄能宽重构图像,验证了所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Narrow-Energy-Width CT Based on Multivoltage X-Ray Image Decomposition.

Narrow-Energy-Width CT Based on Multivoltage X-Ray Image Decomposition.

Narrow-Energy-Width CT Based on Multivoltage X-Ray Image Decomposition.

Narrow-Energy-Width CT Based on Multivoltage X-Ray Image Decomposition.

A polychromatic X-ray beam causes the grey of the reconstructed image to depend on its position within a solid and the material being imaged. This factor makes quantitative measurements via computed tomography (CT) imaging very difficult. To obtain a narrow-energy-width reconstructed image, we propose a model to decompose multivoltage X-ray images into many narrow-energy-width X-ray images by utilizing the low frequency characteristics of X-ray scattering. It needs no change of hardware in the typical CT system. Solving the decomposition model, narrow-energy-width projections are obtained and it is used to reconstruct the image. A cylinder composed of aluminum and silicon is used in a verification experiment. Some of the reconstructed images could be regarded as real narrow-energy-width reconstructed images, which demonstrates the effectiveness of the proposed method.

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来源期刊
CiteScore
12.00
自引率
0.00%
发文量
11
审稿时长
20 weeks
期刊介绍: The International Journal of Biomedical Imaging is managed by a board of editors comprising internationally renowned active researchers. The journal is freely accessible online and also offered for purchase in print format. It employs a web-based review system to ensure swift turnaround times while maintaining high standards. In addition to regular issues, special issues are organized by guest editors. The subject areas covered include (but are not limited to): Digital radiography and tomosynthesis X-ray computed tomography (CT) Magnetic resonance imaging (MRI) Single photon emission computed tomography (SPECT) Positron emission tomography (PET) Ultrasound imaging Diffuse optical tomography, coherence, fluorescence, bioluminescence tomography, impedance tomography Neutron imaging for biomedical applications Magnetic and optical spectroscopy, and optical biopsy Optical, electron, scanning tunneling/atomic force microscopy Small animal imaging Functional, cellular, and molecular imaging Imaging assays for screening and molecular analysis Microarray image analysis and bioinformatics Emerging biomedical imaging techniques Imaging modality fusion Biomedical imaging instrumentation Biomedical image processing, pattern recognition, and analysis Biomedical image visualization, compression, transmission, and storage Imaging and modeling related to systems biology and systems biomedicine Applied mathematics, applied physics, and chemistry related to biomedical imaging Grid-enabling technology for biomedical imaging and informatics
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