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基于电穿孔消融的多模态图像中基于补丁的视场匹配。

Patch-based field-of-view matching in multi-modal images for electroporation-based ablations.

机构信息

University of Bordeaux, IMB, UMR CNRS 5251, INRIA Project team Monc, F-33405 Talence Cedex, France.

University of Bordeaux, IMS, CNRS UMR 5218, F-33405 Talence Cedex, France.

出版信息

Comput Med Imaging Graph. 2020 Sep;84:101750. doi: 10.1016/j.compmedimag.2020.101750. Epub 2020 Jun 16.

Abstract

Various multi-modal imaging sensors are currently involved at different steps of an interventional therapeutic work-flow. Cone beam computed tomography (CBCT), computed tomography (CT) or Magnetic Resonance (MR) images thereby provides complementary functional and/or structural information of the targeted region and organs at risk. Merging this information relies on a correct spatial alignment of the observed anatomy between the acquired images. This can be achieved by the means of multi-modal deformable image registration (DIR), demonstrated to be capable of estimating dense and elastic deformations between images acquired by multiple imaging devices. However, due to the typically different field-of-view (FOV) sampled across the various imaging modalities, such algorithms may severely fail in finding a satisfactory solution. In the current study we propose a new fast method to align the FOV in multi-modal 3D medical images. To this end, a patch-based approach is introduced and combined with a state-of-the-art multi-modal image similarity metric in order to cope with multi-modal medical images. The occurrence of estimated patch shifts is computed for each spatial direction and the shift value with maximum occurrence is selected and used to adjust the image field-of-view. The performance of the proposed method - in terms of both registration accuracy and computational needs - is analyzed in the practical case of on-line irreversible electroporation procedures. In total, 30 pairs of pre-/per-operative IRE images are considered to illustrate the efficiency of our algorithm. We show that a regional registration approach using voxel patches provides a good structural compromise between the voxel-wise and "global shifts" approaches. The method was thereby beneficial for CT to CBCT and MRI to CBCT registration tasks, especially when highly different image FOVs are involved. Besides, the benefit of the method for CT to CBCT and MRI to CBCT image registration is analyzed, including the impact of artifacts generated by percutaneous needle insertions. Additionally, the computational needs using commodity hardware are demonstrated to be compatible with clinical constraints in the practical case of on-line procedures. The proposed patch-based workflow thus represents an attractive asset for DIR at different stages of an interventional procedure.

摘要

目前,各种多模态成像传感器在介入治疗工作流程的不同步骤中都有涉及。锥形束计算机断层扫描(CBCT)、计算机断层扫描(CT)或磁共振(MR)图像因此提供了目标区域和风险器官的互补功能和/或结构信息。合并这些信息依赖于在采集图像之间正确对齐观察到的解剖结构的空间位置。这可以通过多模态可变形图像配准(DIR)来实现,该方法已被证明能够估计来自多个成像设备的图像之间的密集和弹性变形。然而,由于各种成像模式下典型的不同视野(FOV)采样,此类算法可能会严重无法找到满意的解决方案。在本研究中,我们提出了一种新的快速方法来对齐多模态 3D 医学图像的 FOV。为此,引入了基于补丁的方法,并结合了最先进的多模态图像相似性度量标准,以应对多模态医学图像。针对每个空间方向计算估计的补丁移位的发生,并选择具有最大发生的移位值并用于调整图像视野。在在线不可逆电穿孔(IRE)程序的实际情况下,分析了所提出方法在配准准确性和计算需求方面的性能。总共考虑了 30 对术前/术中 IRE 图像,以说明我们算法的效率。我们表明,使用体素补丁的区域配准方法在体素和“全局移位”方法之间提供了良好的结构折衷。该方法因此有益于 CT 到 CBCT 和 MRI 到 CBCT 配准任务,尤其是当涉及高度不同的图像 FOV 时。此外,还分析了该方法对 CT 到 CBCT 和 MRI 到 CBCT 图像配准的益处,包括经皮针插入产生的伪影的影响。此外,还证明了在在线手术的实际情况下,使用商品硬件的计算需求与临床约束兼容。因此,所提出的基于补丁的工作流程代表了介入治疗过程中不同阶段 DIR 的有吸引力的资产。

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