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FPGA-Accelerated Deformable Image Registration for Improved Target-Delineation During CT-Guided Interventions

机译:FPGA加速的可变形图像配准,可在CT引导下进行干预,改善目标描述

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Minimally invasive image-guided interventions (IGIs) are time and cost efficient, minimize unintended damage to healthy tissue, and lead to faster patient recovery. With the advent of multislice computed tomography (CT), many IGIs are now being performed under volumetric CT guidance. Registering pre-and intraprocedural images for improved intraprocedural target delineation is a fundamental need in the IGI workflow. Earlier approaches to meet this need primarily employed rigid body approximation, which may not be valid because of nonrigid tissue misalignment between these images. Intensity-based automatic deformable registration is a promising option to correct for this misalignment; however, the long execution times of these algorithms have prevented their use in clinical workflow. This article presents a field-programmable gate array-based architecture for accelerated implementation of mutual information (Ml)-based deformable registration. The reported implementation reduces the execution time of MI-based deformable registration from hours to a few minutes. This work also demonstrates successful registration of abdominal intraprocedural noncontrast CT (iCT) images with preprocedural contrast-enhanced CT (preCT) and positron emission tomography (PET) images using the reported solution. The registration accuracy for this application was evaluated using 5 iCT-preCT and 5 iCT-PET image pairs. The registration accuracy of the hardware implementation is comparable with that achieved using a software implementation and is on the order of a few millimeters. This registration accuracy, coupled with the execution speed and compact implementation of the reported solution, makes it suitable for integration in the IGI-workflow.
机译:微创图像引导干预(IGI)具有时间和成本效益,可最大程度地减少对健康组织的意外伤害,并可以使患者更快地康复。随着多层计算机断层扫描(CT)的出现,许多IGI正在体积CT引导下进行。在IGI工作流程中,基本需要记录前过程中和过程中的图像以改进过程中目标的轮廓。满足此需求的较早方法主要是采用刚体近似,由于这些图像之间的非刚性组织未对准,这可能无效。基于强度的自动可变形配准是纠正这种失准的有前途的选择。但是,这些算法的执行时间较长,因此无法在临床工作流程中使用它们。本文提出了一种基于现场可编程门阵列的架构,用于加速实现基于互信息(M1)的可变形配准。报告的实现将基于MI的可变形配准的执行时间从几小时减少到了几分钟。这项工作还证明了使用所报道的解决方案成功地将腹腔内非对比CT(iCT)图像与术前对比增强CT(preCT)和正电子发射断层扫描(PET)图像进行配准。使用5个iCT-preCT和5个iCT-PET图像对评估了该应用程序的套准精度。硬件实现的配准精度可与使用软件实现的配准精度相媲美,约为几毫米。这种注册的准确性,再加上所报告解决方案的执行速度和紧凑的实现,使其非常适合集成到IGI工作流中。

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