Incorporating Tissue Excision in Deformable Image Registration: A Modified Demons Algorithm for Cone-Beam CT-Guided Surgery.
Incorporating Tissue Excision in Deformable Image Registration: A Modified Demons Algorithm for Cone-Beam CT-Guided Surgery.
复制标题
将组织切除纳入可变形图像配准：锥束 CT 引导手术的改进恶魔算法。
DOI：
10.1117/12.878258
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
Siewerdsen,JH
中科院分区：
文献类型：
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作者：
Nithiananthan,S;Mirota,D;Uneri,A;Schafer,S;Otake,Y;Stayman,JW;Siewerdsen,JH
研究了在锥形束CT（CBCT）引导的头颈部手术中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。现有的可变形配准方法通常不能考虑在图像采集之间切除的组织，并且通常简单地“移动”图像内的体素，而不能考虑在扫描之间被移除（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额外的维度，以作为在手术过程中移除的体素的汇。使用原型CBCT C形臂采集的一系列尸体图像用于模拟外科手术期间发生的组织变形和切除，并研究了变形配准在这些条件下正确解释解剖结构变化的能力。使用以前开发的版本的恶魔变形配准算法，我们确定了传统的配准算法遇到的困难，当面对切除的组织，并提出了一个修改后的版本的算法更适合用于术中图像引导程序。对不同的变形和组织切除任务进行了研究，并根据准确解释组织切除同时避免切除周围产生虚假变形的能力对配准性能进行了量化。
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.