Spectral Differential Phase Contrast X-Ray Radiography

IF 8.9 1区医学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

IEEE Transactions on Medical Imaging Pub Date : 2020-03-01 DOI:10.1109/TMI.2019.2932450

K. Mechlem, T. Sellerer, M. Viermetz, J. Herzen, F. Pfeiffer

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引用次数: 10

Abstract

We investigate the combination of two emerging X-ray imaging technologies, namely spectral imaging and differential phase contrast imaging. By acquiring spatially and temporally registered images with several different X-ray spectra, spectral imaging can exploit differences in the energy-dependent attenuation to generate material selective images. Differential phase contrast imaging uses an entirely different contrast generation mechanism: The phase shift that an X-ray wave exhibits when traversing an object. As both methods can determine the (projected) electron density, we propose a novel material decomposition algorithm that uses the spectral and the phase contrast information simultaneously. Numerical experiments show that the combination of these two imaging techniques benefits from the strengths of the individual methods while the weaknesses are mitigated: Quantitatively accurate basis material images are obtained and the noise level is strongly reduced, compared to conventional spectral X-ray imaging.

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光谱微分相位对比X射线照相术

我们研究了两种新兴的X射线成像技术的结合，即光谱成像和差分相位对比成像。通过获取具有几个不同X射线光谱的空间和时间配准图像，光谱成像可以利用能量相关衰减的差异来生成材料选择性图像。差分相位对比成像使用了一种完全不同的对比度生成机制：X射线波在穿过物体时表现出的相移。由于这两种方法都可以确定（投影的）电子密度，我们提出了一种新的材料分解算法，该算法同时使用光谱和相位对比度信息。数值实验表明，这两种成像技术的结合得益于各自方法的优点，同时也减轻了缺点：与传统的光谱X射线成像相比，获得了定量准确的基底材料图像，并大大降低了噪声水平。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Medical Imaging 医学-成像科学与照相技术

CiteScore

21.80

自引率

5.70%

发文量

637

审稿时长

5.6 months

期刊介绍： The IEEE Transactions on Medical Imaging (T-MI) is a journal that welcomes the submission of manuscripts focusing on various aspects of medical imaging. The journal encourages the exploration of body structure, morphology, and function through different imaging techniques, including ultrasound, X-rays, magnetic resonance, radionuclides, microwaves, and optical methods. It also promotes contributions related to cell and molecular imaging, as well as all forms of microscopy. T-MI publishes original research papers that cover a wide range of topics, including but not limited to novel acquisition techniques, medical image processing and analysis, visualization and performance, pattern recognition, machine learning, and other related methods. The journal particularly encourages highly technical studies that offer new perspectives. By emphasizing the unification of medicine, biology, and imaging, T-MI seeks to bridge the gap between instrumentation, hardware, software, mathematics, physics, biology, and medicine by introducing new analysis methods. While the journal welcomes strong application papers that describe novel methods, it directs papers that focus solely on important applications using medically adopted or well-established methods without significant innovation in methodology to other journals. T-MI is indexed in Pubmed® and Medline®, which are products of the United States National Library of Medicine.