首页> 外文期刊>European Journal of Radiology >Image fusion in dual energy computed tomography for detection of various anatomic structures--effect on contrast enhancement, contrast-to-noise ratio, signal-to-noise ratio and image quality.
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Image fusion in dual energy computed tomography for detection of various anatomic structures--effect on contrast enhancement, contrast-to-noise ratio, signal-to-noise ratio and image quality.

机译:双能计算机断层扫描中的图像融合可检测各种解剖结构-对对比度增强,对比度噪声比,信噪比和图像质量的影响。

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OBJECTIVE: The purpose of this study was to evaluate image fusion in dual energy computed tomography for detecting various anatomic structures based on the effect on contrast enhancement, contrast-to-noise ratio, signal-to-noise ratio and image quality. MATERIAL AND METHODS: Forty patients underwent a CT neck with dual energy mode (DECT under a Somatom Definition flash Dual Source CT scanner (Siemens, Forchheim, Germany)). Tube voltage: 80-kV and Sn140-kV; tube current: 110 and 290 mAs; collimation-2x32x0.6 mm. Raw data were reconstructed using a soft convolution kernel (D30f). Fused images were calculated using a spectrum of weighting factors (0.0, 0.3, 0.6 0.8 and 1.0) generating different ratios between the 80- and Sn140-kV images (e.g. factor 0.6 corresponds to 60% of their information from the 80-kV image, and 40% from the Sn140-kV image). CT values and SNRs measured in the ascending aorta, thyroid gland, fat, muscle, CSF, spinal cord, bone marrow and brain. In addition, CNR values calculated for aorta, thyroid, muscle and brain. Subjective image quality evaluated using a 5-point grading scale. Results compared using paired t-tests and nonparametric-paired Wilcoxon-Wilcox-test. RESULTS: Statistically significant increases in mean CT values noted in anatomic structures when increasing weighting factors used (all P
机译:目的:本研究旨在评估双能计算机断层扫描中的图像融合,以基于对对比度增强,对比度噪声比,信噪比和图像质量的影响,检测各种解剖结构。材料与方法:40例患者接受了双能量模式的CT颈部检查(在Somatom Definition闪光双源CT扫描仪(德国,福希海姆,Siemens)下进行DECT)。管电压:80-kV和Sn140-kV;灯管电流:110和290 mAs;准直2x32x0.6毫米使用软卷积核(D30f)重建原始数据。使用一系列权重因子(0.0、0.3、0.6 0.8和1.0)计算融合图像,从而在80 kV和Sn140 kV图像之间产生不同的比率(例如,因子0.6对应于80 kV图像中60%的信息, (Sn140-kV图像则为40%)。在升主动脉,甲状腺,脂肪,肌肉,CSF,脊髓,骨髓和脑中测得的CT值和SNRs。此外,还计算了主动脉,甲状腺,肌肉和大脑的CNR值。主观图像质量使用5分等级标度进行评估。使用配对t检验和非参数配对Wilcoxon-Wilcox检验比较结果。结果:当使用增加的加权因子时,解剖结构中的平均CT值具有统计学上的显着增加(所有P

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