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Quantitative evaluation of the performance of different deformable image registration algorithms in helical axial and cone‐beam CT images using a mobile phantom

机译:使用移动体模对螺旋形轴向和锥形束CT图像中不同的可变形图像配准算法的性能进行定量评估

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摘要

The goal of this project is to investigate quantitatively the performance of different deformable image registration algorithms (DIR) with helical (HCT), axial (ACT), and cone‐beam CT (CBCT). The variations in the CT‐number values and lengths of well‐known targets moving with controlled motion were evaluated. Four DIR algorithms: Demons, Fast‐Demons, Horn‐Schunck and Lucas‐Kanade were used to register intramodality CT images of a mobile phantom scanned with different imaging techniques. The phantom had three water‐equivalent targets inserted in a low‐density foam with different lengths (10–40 mm) and moved with adjustable motion amplitudes (0–20 mm) and frequencies (0–0.5 Hz). The variations in the CT‐number level, volumes and shapes of these targets were measured from the spread‐out of the CT‐number distributions. In CBCT, most of the DIR algorithms were able to produce the actual lengths of the mobile targets; however, the CT‐number values obtained from the DIR algorithms deviated from the actual CT‐number of the targets. In HCT, the style="fixed-case">DIR algorithms were successful in deforming the images of the mobile targets to the images of the stationary targets producing the style="fixed-case">CT‐number values and lengths of the targets for motion amplitudes <20 mm. Similarly in style="fixed-case">ACT, all style="fixed-case">DIR algorithms produced the actual style="fixed-case">CT‐number values and lengths of the stationary targets for low‐motion amplitudes <15 mm. The optical flow‐based style="fixed-case">DIR algorithms such as the Horn‐Schunck and Lucas‐Kanade performed better than the Demons and Fast‐Demons that are based on attraction forces particularly at large motion amplitudes. In conclusion, most of the style="fixed-case">DIR algorithms did not reproduce well the style="fixed-case">CT‐number values and lengths of the targets in images that have artifacts induced by large motion amplitudes. The deviations in the style="fixed-case">CT‐number values and variations in the volume of the mobile targets in the deformed style="fixed-case">CT images produced by the different style="fixed-case">DIR algorithms need to be considered carefully in the treatment planning for accurate dose calculation dose coverage of the tumor, and sparing of critical structures.
机译:该项目的目标是定量研究具有螺旋(HCT),轴向(ACT)和锥形束CT(CBCT)的不同可变形图像配准算法(DIR)的性能。评估了CT值的值和以受控运动运动的著名目标的长度的变化。四种DIR算法:恶魔,快速恶魔,霍恩·肖克和卢卡斯·卡纳德用于记录使用不同成像技术扫描的移动体模的模内CT图像。幻影有三个与水等效的目标插入到不同长度(10–40 mm)的低密度泡沫中,并以可调整的运动幅度(0–20 mm)和频率(0–0.5 Hz)移动。这些目标的CT数量水平,体积和形状的变化是通过CT数量分布的分布来衡量的。在CBCT中,大多数DIR算法都能够生成移动目标的实际长度。但是,从DIR算法获得的CT编号值与目标的实际CT编号有所不同。在HCT中, style =“ fixed-case”> DIR 算法成功地将移动目标的图像变形为静止目标的图像,从而产生了 style =“ fixed-case”> CT -运动幅度小于20毫米的目标的值和长度。同样,在 style =“ fixed-case”> ACT 中,所有 style =“ fixed-case”> DIR 算法都产生了实际的 style =“ fixed-case”> CT < / span>-小于15 mm的低运动幅度的固定目标的数值和长度。基于光流的 style =“ fixed-case”> DIR 算法(例如Horn-Schunck和Lucas-Kanade)的性能要优于基于吸引力的恶魔和快速恶魔,特别是在大运动中振幅。总之,大多数 style =“ fixed-case”> DIR 算法不能很好地再现目标的 style =“ fixed-case”> CT -数值和长度在具有由大运动幅度引起的伪影的图像中。 style =“ fixed-case”> CT -数量值的偏差和变形的 style =“ fixed-case”> CT 图像中移动目标的体积变化在治疗计划中需要仔细考虑由不同的 style =“ fixed-case”> DIR 算法产生的结果,以准确计算剂量并覆盖肿瘤,并保留关键结构。

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