首页> 外文会议>International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine;Society of Photo-Optical Instrumentation Engineers;Canon Medical Research USA, Inc.;United Imaging Healthcare Group Co., Ltd. >Clinical study of soft-tissue contrast resolution in cone-beam CT of the head using multi-resolution PWLS with multi-motion correction and an electronic noise model
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Clinical study of soft-tissue contrast resolution in cone-beam CT of the head using multi-resolution PWLS with multi-motion correction and an electronic noise model

机译:采用多运动校正和电子噪声模型的多分辨率PWLS在头部锥形束CT中软组织对比分辨率的临床研究

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Purpose: Improving soft-tissue contrast resolution beyond the capability of current cone-beam CT (CBCT) systems isessential to a growing range of image guidance and diagnostic imaging scenarios. We present a framework for CBCTmodel-based image reconstruction (MBIR) combining artifact corrections with multi-resolution reconstruction and multiregionmotion compensation and apply the method for the first time in a clinical study of CBCT for high-quality imagingof head injury.Methods: A CBCT prototype was developed for mobile point-of-care imaging in the neuro-critical care unit (NCCU).Projection data were processed via poly-energetic gain correction and an artifacts correction pipeline treating scatter, beamhardening, and motion compensation. The scatter correction was modified to use a penalized weighted least-squares(PWLS) image in the Monte-Carlo (MC) object model for better uniformity in truncated data. The PWLS method included:(1) multi-resolution reconstruction to mitigate lateral truncation from the head-holder; (2) multi-motion compensationallowing separate motion of the head and head-holder; and (3) modified statistical weights to account for electronics noiseand fluence modulation by the bowtie filter. Imaging performance was evaluated in simulation and in the first clinicalstudy (N = 54 patients) conducted with the system.Results: Using a PWLS object model in the final iteration of the MC scatter estimate improved image uniformity by 40.4%for truncated datasets. The multi-resolution, multi-motion PWLS method greatly reduced streak artifacts and nonuniformityboth in simulation (RMSE reduced by 65.5%) and in the clinical study (visual image quality assessed by aneuroradiologist). Up to 15% reduction in variance was achieved using statistical weights modified according to a modelfor electronic noise from the detector. Each component was important for improved contrast resolution in the patient data.Conclusion: An integrated pipeline for artifacts correction and PWLS reconstruction mitigated artifacts and noise to alevel supporting visualization of low-contrast brain lesions and warranting future studies of diagnostic performance in theNCCU.
机译:目的:改善超出当前锥形梁CT(CBCT)系统的能力的软组织对比度分辨率 对越来越多的图像引导和诊断成像方案至关重要。我们为CBCT提供了一个框架 基于模型的图像重建(MBIR)与多分辨率重建和多限元组合的工件校正 运动补偿并在高质量成像中第一次应用该方法。高质量成像中的临床研究 头部受伤。 方法:开发了CBCT原型,用于在神经关键护理单元(NCCU)中的移动餐点成像。 投影数据通过多量增益校正处理和伪影校正管道处理散射,梁 硬化和运动补偿。散射校正被修改为使用惩罚的加权最小二乘法 (PWLS)在Monte-Carlo(MC)对象模型中的图像,用于更好的截断数据均匀性。包括PWLS方法: (1)多分辨率重建,以减轻头部持有者的横向截断; (2)多运动补偿 允许头部和头部支架的单独运动; (3)修改统计权重,以解释电子噪声 并通过Bowtie滤波器来调节。在模拟和第一个临床中评估了成像性能 用系统进行研究(n = 54名患者)。 结果:在最终迭代中使用PWLS对象模型估计改善图像均匀度为40.4% 对于截断的数据集。多分辨率,多运动PWLS方法大大降低了条纹伪影和不均匀性 仿真(RMSE减少了65.5%)和临床研究(通过A评估的视觉图像质量 神经皮层)。使用根据模型修改的统计重量,实现了差异减少了15% 对于探测器的电子噪声。每个组分对于改善患者数据中的对比度分辨率非常重要。 结论:用于伪影校正的一体化管道和PWLS重建减少了伪影和噪声 水平支持低对比度脑病变的可视化,并保证未来对诊断性能的研究 NCCU。

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