Department of Electrical Engineering, Chang Gung University, Tao-Yuan 333, Taiwan.
Med Phys. 2010 Sep;37(9):4551-9. doi: 10.1118/1.3470097.
In image-guided surgery (IGS) systems, image-to-physical registration is critical for reliable anatomical information mapping and spatial guidance. Conventional stereotactic frame-based or fiducial-based approaches provide accurate registration but are not patient-friendly. This study proposes a frameless cranial IGS system that uses computer vision techniques to replace the frame or fiducials with the natural features of the patient.
To perform a cranial surgery with the proposed system, the facial surface of the patient is first reconstructed by stereo vision. Accuracy is ensured by capturing parallel-line patterns projected from a calibrated LCD projector. Meanwhile, another facial surface is reconstructed from preoperative computed tomography (CT) images of the patient. The proposed iterative closest point (ICP)-based algorithm [fast marker-added ICP (Fast-MICP)] is then used to register the two facial data sets, which transfers the anatomical information from the CT images to the physical space.
Experimental results reveal that the Fast-MICP algorithm reduces the computational cost of marker-added ICP (J.-D. Lee et al., "A coarse-to-fine surface registration algorithm for frameless brain surgery," in Proceedings of International Conference of the IEEE Engineering in Medicine and Biology Society, 2007, pp. 836-839) to 10% and achieves comparable registration accuracy, which is under 3 mm target registration error (TRE). Moreover, two types of optical-based spatial digitizing devices can be integrated for further surgical navigation. Anatomical information or image-guided surgical landmarks can be projected onto the patient to obtain an immersive augmented reality environment.
The proposed frameless IGS system with stereo vision obtains TRE of less than 3 mm. The proposed Fast-MICP registration algorithm reduces registration time by 90% without compromising accuracy.
在图像引导手术（IGS）系统中，图像到物理的配准对于可靠的解剖信息映射和空间引导至关重要。传统的立体定向框架或基于基准的方法提供了精确的配准，但对患者不友好。本研究提出了一种无框架颅骨 IGS 系统，该系统使用计算机视觉技术替代患者的自然特征来代替框架或基准。
为了使用提出的系统进行颅骨手术，首先通过立体视觉重建患者的面部表面。通过捕获从校准的 LCD 投影仪投射的平行线图案来确保准确性。同时，从患者的术前计算机断层扫描（CT）图像重建另一个面部表面。然后，使用基于迭代最近点（ICP）的算法[快速标记添加 ICP（Fast-MICP）]来注册两个面部数据集，将解剖信息从 CT 图像传输到物理空间。
实验结果表明，Fast-MICP 算法将标记添加 ICP（J.-D. Lee 等人，“无框架脑手术的粗到精表面配准算法”，在 IEEE 工程医学与生物学学会国际会议的 Proceedings 中，2007 年，第 836-839 页）的计算成本降低到 10%，并达到了可比的注册精度，目标注册误差（TRE）小于 3 毫米。此外，还可以集成两种类型的基于光学的空间数字化设备，以进行进一步的手术导航。解剖信息或图像引导手术的标志可以投射到患者身上，以获得沉浸式增强现实环境。
提出的具有立体视觉的无框架 IGS 系统的 TRE 小于 3 毫米。所提出的 Fast-MICP 注册算法将注册时间减少了 90%，而不会影响准确性。
