Suppr超能文献

锗小动物单光子发射计算机断层扫描系统的研制

Development of a Germanium Small-Animal SPECT System.

作者信息

Johnson Lindsay C, Ovchinnikov Oleg, Shokouhi Sepideh, Peterson Todd E

机构信息

Vanderbilt University Institute of Imaging Science and the Department of Radiology and Radiological Sciences, Nashville, TN 37232 USA and is now with the University of Pennsylvania Department of Radiology, Philadelphia PA 19104 USA.

Vanderbilt University Institute of Imaging Science and the Department of Physics, Nashville, TN 37232 USA.

出版信息

IEEE Trans Nucl Sci. 2015 Oct;2015:2036-2042. doi: 10.1109/TNS.2015.2448673. Epub 2015 Oct 9.

Abstract

Advances in fabrication techniques, electronics, and mechanical cooling systems have given rise to germanium detectors suitable for biomedical imaging. We are developing a small-animal SPECT system that uses a double-sided Ge strip detector. The detector's excellent energy resolution may help to reduce scatter and simplify processing of multi-isotope imaging, while its ability to measure depth of interaction has the potential to mitigate parallax error in pinhole imaging. The detector's energy resolution is <1% FWHM at 140 keV and its spatial resolution is approximately 1.5 mm FWHM. The prototype system described has a single-pinhole collimator with a 1-mm diameter and a 70-degree opening angle with a focal length variable between 4.5 and 9 cm. Phantom images from the gantry-mounted system are presented, including the NEMA NU-2008 phantom and a hot-rod phantom. Additionally, the benefit of energy resolution is demonstrated by imaging a dual-isotope phantom with Tc and I without cross-talk correction.

摘要

制造技术、电子学和机械冷却系统的进步催生了适用于生物医学成像的锗探测器。我们正在开发一种使用双面锗条探测器的小动物单光子发射计算机断层显像(SPECT)系统。该探测器出色的能量分辨率有助于减少散射并简化多同位素成像的处理,而其测量相互作用深度的能力有可能减轻针孔成像中的视差误差。该探测器在140keV时的能量分辨率为<1%半高宽(FWHM),其空间分辨率约为1.5mm半高宽。所描述的原型系统有一个直径为1mm、开口角度为70度、焦距在4.5至9cm之间可变的单针孔准直器。展示了来自安装在机架上的系统的体模图像,包括NEMA NU - 2008体模和热棒体模。此外,通过对含有锝(Tc)和碘(I)的双同位素体模进行成像且不进行串扰校正,证明了能量分辨率的优势。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验