The distance discordance metric-a novel approach to quantifying spatial uncertainties in intra- and inter-patient deformable image registration.
The distance discordance metric-a novel approach to quantifying spatial uncertainties in intra- and inter-patient deformable image registration.
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DOI：
10.1088/0031-9155/59/3/733
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发表时间：
2014-02-07
影响因子：
3.5
通讯作者：
Deasy JO
中科院分区：
文献类型：
--
作者：
Saleh ZH;Apte AP;Sharp GC;Shusharina NP;Wang Y;Veeraraghavan H;Thor M;Muren LP;Rao SS;Lee NY;Deasy JO
用于估计可变形图像配准（reformable image registration，简称REQ）的固有精度的先前方法通常相对于已知的地面实况（ground truth）来执行，诸如跟踪解剖标志或物理或虚拟体模中的已知变形。在本研究中，我们提出了一种新的方法，使用统计采样技术来估计DIR的空间几何不确定性，该技术可应用于给定配准的变形矢量场（DVF）。所提出的距离不一致性度量（DDM）是基于来自不同图像的对应体素之间的距离的可变性，这些体素在任意选择的“参考”图像中的位置（X）处共同配准到相同体素。当这些图像与图像集中的其他图像配准时，参考图像中位置（X）处的DDM值表示体素之间的平均离散度。该方法需要至少四个注册的图像来估计的DIR的不确定性，无论是患者间和患者内的呼吸。为了验证所提出的方法，我们生成了一个图像集，通过变形的软件幻影与已知的DVF。在“参考”体模中的每个体素处计算配准误差，然后将其与整个体模上的DDM、逆一致性误差（ICE）和传递性误差（TE）进行比较。与ICE和TE相比，DDM显示出更高的Pearson相关（Rp）与实际误差（Rp范围为0.6至0.9）（Rp范围为0.2至0.8）。在所得到的空间DDM图中，具有不同强度梯度的区域具有较低的不一致性，因此相对于具有均匀强度的区域具有较小的变异性。随后，我们将DDM应用于一个前列腺癌患者的10个纵向计算机断层扫描（CT）扫描的图像集中的患者内检查，并应用于不同头颈部癌症患者的10个计划CT扫描的图像集中的患者间检查。对于患者内和患者间的直肠癌，空间DDM图显示了感兴趣体积的较大变化（前列腺患者的骨盆和头颈部患者的头部）。由于配准的变异性较高，在软组织（如脑、膀胱和直肠）中观察到的不一致性最高。在骨盆和颅底的骨性结构中观察到最小的DDM值。建议的度量，DDM，提供了一个定量的工具，以评估性能时，一组图像是可用的。因此，DDM可用于基于配准的可变性而不是绝对配准误差来估计和可视化患者内和/或患者间的不确定性。
Previous methods to estimate the inherent accuracy of deformable image registration (DIR) have typically been performed relative to a known ground truth, such as tracking of anatomic landmarks or known deformations in a physical or virtual phantom. In this study, we propose a new approach to estimate the spatial geometric uncertainty of DIR using statistical sampling techniques that can be applied to the resulting deformation vector fields (DVFs) for a given registration. The proposed DIR performance metric, the distance discordance metric (DDM), is based on the variability in the distance between corresponding voxels from different images, which are co-registered to the same voxel at location (X) in an arbitrarily chosen “reference” image. The DDM value, at location (X) in the reference image, represents the mean dispersion between voxels, when these images are registered to other images in the image set. The method requires at least four registered images to estimate the uncertainty of the DIRs, both for inter-and intra-patient DIR. To validate the proposed method, we generated an image set by deforming a software phantom with known DVFs. The registration error was computed at each voxel in the “reference” phantom and then compared to DDM, inverse consistency error (ICE), and transitivity error (TE) over the entire phantom. The DDM showed a higher Pearson correlation (Rp) with the actual error (Rp ranged from 0.6 to 0.9) in comparison with ICE and TE (Rp ranged from 0.2 to 0.8). In the resulting spatial DDM map, regions with distinct intensity gradients had a lower discordance and therefore, less variability relative to regions with uniform intensity. Subsequently, we applied DDM for intra-patient DIR in an image set of 10 longitudinal computed tomography (CT) scans of one prostate cancer patient and for inter-patient DIR in an image set of 10 planning CT scans of different head and neck cancer patients. For both intra- and inter-patient DIR, the spatial DDM map showed large variation over the volume of interest (the pelvis for the prostate patient and the head for the head and neck patients). The highest discordance was observed in the soft tissues, such as the brain, bladder, and rectum, due to higher variability in the registration. The smallest DDM values were observed in the bony structures in the pelvis and the base of the skull. The proposed metric, DDM, provides a quantitative tool to evaluate the performance of DIR when a set of images is available. Therefore, DDM can be used to estimate and visualize the uncertainty of intra- and/or inter-patient DIR based on the variability of the registration rather than the absolute registration error.
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影响因子：
3.5
作者：
Acosta, Oscar;Drean, Gael;de Crevoisier, Renaud
通讯作者：
de Crevoisier, Renaud
DOI：
10.1186/1748-717x-8-154
发表时间：
2013-06-26
期刊：
Radiation oncology (London, England)
影响因子：
--
作者：
Daisne JF;Blumhofer A
通讯作者：
Blumhofer A
影响因子：
10.6
作者：
Kybic, Jan
通讯作者：
Kybic, Jan
DOI：
10.1186/1748-717x-6-73
发表时间：
2011-06-16
期刊：
Radiation oncology (London, England)
影响因子：
--
作者：
Jonsson JH;Brynolfsson P;Garpebring A;Karlsson M;Söderström K;Nyholm T
通讯作者：
Nyholm T
DOI：
10.1186/1748-717x-7-90
发表时间：
2012-06-15
期刊：
Radiation oncology (London, England)
影响因子：
--
作者：
Hardcastle N;Tomé WA;Cannon DM;Brouwer CL;Wittendorp PW;Dogan N;Guckenberger M;Allaire S;Mallya Y;Kumar P;Oechsner M;Richter A;Song S;Myers M;Polat B;Bzdusek K
通讯作者：
Bzdusek K