Institute of Micro Technology and Medical Device Technology, Technische Universität München, 85748 Garching, Germany.
IEEE Trans Biomed Eng. 2011 Oct;58(10):2922-30. doi: 10.1109/TBME.2011.2163156. Epub 2011 Jul 29.
Surgical navigation systems are used widely among all fields of modern medicine, including, but not limited to ENT- and maxillofacial surgery. As a fundamental prerequisite for image-guided surgery, intraoperative registration, which maps image to patient coordinates, has been subject to many studies and developments. While registration methods have evolved from invasive procedures like fixed stereotactic frames and implanted fiducial markers toward surface-based registration and noninvasive markers fixed to the patient's skin, even the most sophisticated registration techniques produce an imperfect result. Due to errors introduced during the registration process, the projection of navigated instruments into image data deviates up to several millimeter from the actual position, depending on the applied registration method and the distance between the instrument and the fiducial markers. We propose a method that allows to automatically and continually improve registration accuracy during intraoperative navigation after the actual registration process has been completed. The projections of navigated instruments into image data are inspected and validated by the navigation software. Errors in image-to-patient registration are identified by calculating intersections between the virtual instruments' axes and surfaces of hard bone tissue extracted from the patient's image data. The information gained from the identification of such registration errors is then used to improve registration accuracy by adding an additional pair of registration points at every location where an error has been detected. The proposed method was integrated into a surgical navigation system based on paired points registration with anatomical landmarks. Experiments were conducted, where registrations with deliberately misplaced point pairs were corrected with automatic error correction. Results showed an improvement in registration quality in all cases.
手术导航系统广泛应用于现代医学的各个领域，包括但不限于耳鼻喉科和颌面外科。作为图像引导手术的基本前提，将图像映射到患者坐标的术中配准已经经过了许多研究和发展。虽然配准方法已经从固定立体定向框架和植入的基准标记等侵入性程序发展到基于表面的配准和固定在患者皮肤上的非侵入性标记，但即使是最复杂的配准技术也无法达到完美的效果。由于配准过程中引入的误差，导航器械在图像数据中的投影与实际位置相差可达数毫米，具体取决于所应用的配准方法和器械与基准标记之间的距离。我们提出了一种方法，允许在实际配准过程完成后，在术中导航期间自动和持续地提高配准精度。导航软件会检查和验证导航器械在图像数据中的投影。通过计算虚拟器械轴与从患者图像数据中提取的硬骨组织表面之间的交点，可以识别图像到患者配准中的误差。然后，利用从这种配准误差识别中获得的信息，通过在检测到误差的每个位置添加一对额外的配准点来提高配准精度。所提出的方法已集成到基于解剖学标志点的配准的手术导航系统中。进行了实验，其中故意错位的点对的配准通过自动误差校正进行了校正。结果表明，在所有情况下，配准质量都有所提高。
