Respiratory motion correction in free-breathing ultrasound image sequence for quantification of hepatic perfusion.
Respiratory motion correction in free-breathing ultrasound image sequence for quantification of hepatic perfusion.
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DOI：
10.1118/1.3606456
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发表时间：
2011-08
期刊：
影响因子：
3.8
通讯作者：
Ji Zhang;Mingyue Ding;Fan Meng;M. Yuchi;Xuming Zhang
中科院分区：
文献类型：
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作者：
Ji Zhang;Mingyue Ding;Fan Meng;M. Yuchi;Xuming Zhang
目的通过超声造影（CEUS）评估局部肝脏灌注有助于肝脏局灶性病变（FLL）的鉴别诊断。由于大多数患者在整个肝脏灌注扫描过程中无法屏住呼吸，因此超声医师倾向于采用自由呼吸采集方法。提出了一种结合模板匹配和帧选择的新策略来校正呼吸运动并提高灌注量化评估的准确性。方法考虑到大多数商用超声机可以提供双显示模式以同时可视化对比图像和组织图像，对比图像的配准是通过相应组织图像的配准来实现的。定位模板后，使用自由呼吸图像序列中肿瘤位置的先验知识来估计粗略搜索空间。然后，提出了一种简单的双选择方法，通过全局和局部阈值设置从大量连续匹配图像中选择相似图像。该方法中，α和m分别是全局阈值的偏移量和设置局部采样范围的时间间隔。还对这两个参数进行了研究。该策略使用绝对差之和 (SAD) 指标，通过手柄探针对 10 次肝脏 CEUS 采集进行了测试。对二维图像序列进行视觉评估并从感兴趣区域提取时间-强度曲线。运动未校正和运动校正图像序列的更简单的曲线描述符是在逐像素的基础上计算的，并作为参数灌注图进行评估。在精度和空间分辨率方面对这些参数图像的质量进行了比较。对于校正和未校正的序列，测量了它们的平均偏差值（mDV）和平均拟合质量（mQOF）。结果当 alpha 和 m 均设置为 0.5 时，选择了帧总数的 9.20 +/- 3.22%。运动校正后，所有图像序列的 mDV 从 21.69 +/- 2.80 下降到 13.78 +/- 2.68。所有校正序列的 mQOF 平均增加了 15.32 +/- 5.13%。曲线拟合的质量和在运动校正序列上计算的相应参数成像得到了提高。平均而言，使用 MATLAB 对包含约 100 帧的序列进行运动校正大约需要 3 分钟，而完全手动的方法需要大约 10 分钟。结论 独立于肿瘤大小的基于图像的策略可以快速纠正 CEUS 图像序列中的呼吸运动。只需要简单的手动操作，例如模板图像的选择和搜索空间。界面友好，适用于大多数受采样不利因素影响的临床病例。由于节省时间的优点，该策略可以广泛应用于临床实践，并且将提高FLL的诊断效率。此外，校正策略是肝灌注研究局部量化的关键预处理步骤。
PURPOSE Evaluation of regional hepatic perfusion by contrast-enhanced ultrasound (CEUS) is helpful to the differential diagnosis of focal liver lesions (FLLs). Because most patients cannot hold their breath for the duration of the entire hepatic perfusion scan, ultrasonographists tend to employ free-breathing acquisition method. A new strategy using a combination of template matching and frame selection is proposed to correct the respiratory motion and improve the accuracy of the quantification evaluation of the perfusion. METHODS Considering that most commercial ultrasound machines can provide a dual display mode for simultaneously visualizing contrast and tissue images, the registration of the contrast images was achieved by the registration of the corresponding tissue images. After the template was located, the rough search space was estimated using a priori knowledge of the tumor location in the free-breathing image sequence. Then, a simple double-selection method was proposed to select the similar images from a large number of successive matched images via global and local threshold settings. In this method, alpha and m were the offset of the global threshold and the time interval for setting local sampling range, respectively. These two parameters were also investigated. The strategy was tested on ten liver CEUS acquisitions with a handle probe by using sum of absolute differences (SAD) metric. The visual evaluation for 2D image sequences and the extracted time-intensity curves from the regions of interest were performed. Simpler curve descriptors of the motion-uncorrected and motion-corrected image sequences were calculated on a pixel-by-pixel basis and evaluated as parametric perfusion maps. The quality of these parametric images was compared, in terms of both the accuracy and spatial resolution. For the corrected and uncorrected sequences, their mean deviation values (mDVs) and mean quality-of-fits (mQOFs) were measured. RESULTS When alpha and m were both set to 0.5, 9.20 +/- 3.22% of the total number of frames were selected. After the motion correction, the mDVs of all the image sequences decreased from 21.69 +/- 2.80 to 13.78 +/- 2.68. The mQOFs of all the corrected sequences increased by an average of 15.32 +/- 5.13%. The quality of curve fitting and the corresponding parametric imaging computed on motion-corrected sequences were improved. On the average, the motion correction of a sequence containing about 100 frames was performed in approximately 3 min using MATLAB, whereas a completely manual approach requires approximately 10 min. CONCLUSIONS The image-based strategy independent of the tumor size can quickly correct respiratory motion in CEUS image sequences. Simple manual operation is only needed, such as the selection of the template image and search space. It is user-friendly and suitable for most clinical cases affected by adverse factors of sampling. Due to the merit of the saving time, this strategy can be widely applied to clinical practice, and the diagnostic efficiency of FLLs will be improved. Moreover, the correction strategy is a key preprocessing step toward local quantification of hepatic perfusion studies.