Automatic intrinsic cardiac and respiratory gating from cone-beam CT scans of the thorax region
Automatic intrinsic cardiac and respiratory gating from cone-beam CT scans of the thorax region
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通过胸部区域的锥束 CT 扫描自动进行心脏内在门控和呼吸门控
DOI：
10.1117/12.2216224
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
M. Kachelrieß
中科院分区：
文献类型：
--
作者：
A. Hahn;S. Sauppe;M. Lell;M. Kachelrieß
我们提出了一种新的算法，允许在锥束CT扫描中基于原始数据的自动心脏和呼吸内在门控。它可以概括为三个步骤：首先，中值滤波器应用于初始重建的体积。该体积的前向投影包含较少的运动信息，并从原始投影中减去。这导致新的原始数据仅包含移动而不包含静态解剖结构（如骨骼），否则会妨碍心脏或呼吸信号采集。所有进一步的步骤都应用于这些修改后的原始数据。其次，将原始数据裁剪到感兴趣区域（ROI）。原始数据中的ROI由二进制感兴趣体积（VOI）的前向投影确定，该二进制感兴趣体积包括用于呼吸门控的隔膜和用于心脏门控的心脏的大部分边缘。第三，针对每个投影计算该ROI中的平均灰度值，并且使用带通滤波器采集呼吸/心脏信号。步骤二和步骤三分别针对呼吸或心脏信号在身体内的64或1440个重叠VOI同时执行。比较从每个ROI采集的信号，并选择最一致的信号作为所需的心脏或呼吸运动信号。通过两个最大值之间时间的标准差评估一致性。该方法的鲁棒性和效率使用模拟和测量的患者数据进行评估，通过计算的标准偏差的平均信号之间的差异的地面真相和内在的信号。
We present a new algorithm that allows for raw data-based automated cardiac and respiratory intrinsic gating in cone-beam CT scans. It can be summarized in three steps: First, a median filter is applied to an initially reconstructed volume. The forward projection of this volume contains less motion information and is subtracted from the original projections. This results in new raw data that contain only moving and not static anatomy like bones, that would otherwise impede the cardiac or respiratory signal acquisition. All further steps are applied to these modified raw data. Second, the raw data are cropped to a region of interest (ROI). The ROI in the raw data is determined by the forward projection of a binary volume of interest (VOI) that includes the diaphragm for respiratory gating and most of the edge of the heart for cardiac gating. Third, the mean gray value in this ROI is calculated for every projection and the respiratory/cardiac signal is acquired using a bandpass filter. Steps two and three are carried out simultaneously for 64 or 1440 overlapping VOI inside the body for the respiratory or cardiac signal respectively. The signals acquired from each ROI are compared and the most consistent one is chosen as the desired cardiac or respiratory motion signal. Consistency is assessed by the standard deviation of the time between two maxima. The robustness and efficiency of the method is evaluated using simulated and measured patient data by computing the standard deviation of the mean signal difference between the ground truth and the intrinsic signal.
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影响因子：
3.5
作者：
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