Automatic localization of vertebral levels in x-ray fluoroscopy using 3D-2D registration: a tool to reduce wrong-site surgery.
Automatic localization of vertebral levels in x-ray fluoroscopy using 3D-2D registration: a tool to reduce wrong-site surgery.
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使用3D-2D登记：减少错误位点手术的工具，将椎骨荧光镜检查中椎骨水平自动定位。
DOI：
10.1088/0031-9155/57/17/5485
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发表时间：
2012-09-07
影响因子：
3.5
通讯作者：
Siewerdsen JH
中科院分区：
文献类型：
--
作者：
Otake Y;Schafer S;Stayman JW;Zbijewski W;Kleinszig G;Graumann R;Khanna AJ;Siewerdsen JH
手术定位于不正确的椎体节段(“错误节段”手术)是更常见的错误部位手术错误之一，主要归因于在胸椎中部缺乏唯一可识别的放射学标志。传统的定位方法需要在透视下人工计数椎体，容易发生人为错误，并且需要额外的时间和剂量。我们提出了一个图像配准和可视化系统(称为LevelCheck)，通过使用GPU加速的、基于强度的3D-2D(即，CT到透视)配准，在透视中自动标记椎体水平，用于脊柱手术的决策支持。选择了梯度信息(GI)相似性度量和CMA-ES优化器，因为它们具有健壮性和内在的并行化适应性。模拟研究涉及10个患者CT数据集，从其中生成50,000个模拟C臂姿势的透视图像，以近似C臂操作者和位置变异性。物理实验使用了一个在真实透视下拍摄的拟人胸腔模型。配准精度以估计的椎体平面中心与真实椎体平面中心之间的平均投影距离(MPD)来评估。如果估计的位置在椎体的投影范围内(即MPD<；5 mm)，则试验被定义为成功。模拟研究显示，在中端GPU上，成功率为99.998%(50,000次试验中有1次失败)，计算时间为4.7秒。失效模式分析识别了由于脊椎结构的纵向周期性而在搜索空间中产生的虚假局部最优的情况。物理实验表明，该算法对量子噪声和X射线散射具有较强的鲁棒性。在透视中近实时地自动定位目标解剖的能力在减少错误部位手术的发生同时帮助减少辐射暴露方面可能是有价值的。该方法不仅适用于脊椎标记的特定情况，因为术前(或术中)CT或锥束CT中定义的任何结构都可以自动配准到透视场景。
Surgical targeting of the incorrect vertebral level (“wrong-level” surgery) is among the more common wrong-site surgical errors, attributed primarily to a lack of uniquely identifiable radiographic landmarks in the mid-thoracic spine. Conventional localization method involves manual counting of vertebral bodies under fluoroscopy, is prone to human error, and carries additional time and dose. We propose an image registration and visualization system (referred to as LevelCheck), for decision support in spine surgery by automatically labeling vertebral levels in fluoroscopy using a GPU-accelerated, intensity-based 3D-2D (viz., CT-to-fluoroscopy) registration. A gradient information (GI) similarity metric and CMA-ES optimizer were chosen due to their robustness and inherent suitability for parallelization. Simulation studies involved 10 patient CT datasets from which 50,000 simulated fluoroscopic images were generated from C-arm poses selected to approximate C-arm operator and positioning variability. Physical experiments used an anthropomorphic chest phantom imaged under real fluoroscopy. The registration accuracy was evaluated as the mean projection distance (mPD) between the estimated and true center of vertebral levels. Trials were defined as successful if the estimated position was within the projection of the vertebral body (viz., mPD < 5mm). Simulation studies showed a success rate of 99.998% (1 failure in 50,000 trials) and computation time of 4.7 sec on a midrange GPU. Analysis of failure modes identified cases of false local optima in the search space arising from longitudinal periodicity in vertebral structures. Physical experiments demonstrated robustness of the algorithm against quantum noise and x-ray scatter. The ability to automatically localize target anatomy in fluoroscopy in near-real-time could be valuable in reducing the occurrence of wrong-site surgery while helping to reduce radiation exposure. The method is applicable beyond the specific case of vertebral labeling, since any structure defined in pre-operative (or intra-operative) CT or cone-beam CT can be automatically registered to the fluoroscopic scene.
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影响因子：
10.6
作者：
Otake Y;Armand M;Armiger RS;Kutzer MD;Basafa E;Kazanzides P;Taylor RH
通讯作者：
Taylor RH
影响因子：
3.8
作者：
Birkfellner W;Stock M;Figl M;Gendrin C;Hummel J;Dong S;Kettenbach J;Georg D;Bergmann H
通讯作者：
Bergmann H
影响因子：
--
作者：
Hsu, Wesley;Sciubba, Daniel M.;Murphy, Kieran
通讯作者：
Murphy, Kieran
影响因子：
3.8
作者：
Jin, Jian-Yue;Ryu, Samuel;Movsas, Benjamin
通讯作者：
Movsas, Benjamin
DOI：
10.1007/s11548-008-0264-z
发表时间：
2008-12-01
影响因子：
3
作者：
Hurvitz, Aviv;Joskowicz, Leo
通讯作者：
Joskowicz, Leo