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Incorporating Tissue Excision in Deformable Image Registration:A Modified Demons Algorithm for Cone-Beam CT-Guided Surgery

机译:将组织切除结合到可变形图像配准中:锥束CT引导手术的改良恶魔算法

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The ability to perform fast, accurate, deformable registration with intraoperative images featuring surgical excisions was investigated for use in cone-beam CT (CBCT) guided head and neck surgery. Existing deformable registration methods generally fail to account for tissue excised between image acquisitions and typically simply "move" voxels within the images with no ability to account for tissue that is removed (or introduced) between scans. We have thus developed an approach in which an extra dimension is added during the registration process to act as a sink for voxels removed during the course of the procedure. A series of cadaveric images acquired using a prototype CBCT-capable C-arm were used to model tissue deformation and excision occurring during a surgical procedure, and the ability of deformable registration to correctly account for anatomical changes under these conditions was investigated. Using a previously developed version of the Demons deformable registration algorithm, we identify the difficulties that traditional registration algorithms encounter when faced with excised tissue and present a modified version of the algorithm better suited for use in intraoperative image-guided procedures. Studies were performed for different deformation and tissue excision tasks, and registration performance was quantified in terms of the ability to accurately account for tissue excision while avoiding spurious deformations arising around the excision.
机译:研究了使用具有手术切除特征的术中图像进行快速,准确,可变形配准的能力,以用于锥形束CT(CBCT)引导的头颈部手术。现有的可变形配准方法通常不能解决在图像获取之间切除的组织,并且通常不能简单地“移动”图像内的体素,而无法解决在两次扫描之间被去除(或引入)的组织。因此,我们开发了一种方法,其中在配准过程中添加了额外的尺寸,以充当在过程中移除的体素的接收器。使用具有原型CBCT功能的C型臂采集的一系列尸体图像用于模拟外科手术过程中发生的组织变形和切除,并研究了在这些情况下可变形配准正确解释解剖变化的能力。使用先前开发的恶魔可变形配准算法版本,我们确定了传统配准算法在面对切除的组织时遇到的困难,并提出了该算法的改进版本,更适合在术中图像引导手术中使用。针对不同的变形和组织切除任务进行了研究,并根据准确说明组织切除的能力(同时避免了切除周围出现的假性变形)对配准性能进行了量化。

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