Bucholz R, Macneil W, Fewings P, Ravindra A, McDurmont L, Baumann C
CRNFA Jean H. Bakewell Section of Image Guided Surgery, Department of Surgery, Saint Louis University School of Medicine, MO 63104, USA.
Stud Health Technol Inform. 2000;70:39-45.
Most image guided Neurosurgery employs adhesively mounted external fiducials for registration of medical images to the surgical workspace. Due to high logistical costs associated with these artificial landmarks, we strive to eliminate the need for these markers. At our institution, we developed a handheld laser stripe triangulation device to capture the surface contours of the patient's head while oriented for surgery. Anatomical surface registration algorithms rely on the assumption that the patient's anatomy bears the same geometry as the 3D model of the patient constructed from the imaging modality employed. During the time interval from which the patient is imaged and placed in the Mayfield head clamp in the operating room, the skin of the head bulges at the pinsite and the skull fixation equipment itself optically interferes with the image capture laser. We have developed software to reject points belonging to objects of known geometry while calculating the registration. During the course of development of the laser scanning unit, we have acquired surface contours of 13 patients and 2 cadavers. Initial analysis revealed that this automated rejection of points improved the registrations in all cases, but the accuracy of the fiducial method was not surpassed. Only points belonging to the offending instrument are removed. Skin bulges caused by the clamps and instruments remain in the data. We anticipate that careful removal of the points in these skin bulges will yield registrations that at least match the accuracy of the fiducial method.
大多数图像引导神经外科手术采用粘贴式外部基准标记，用于将医学图像配准到手术工作空间。由于与这些人工标记相关的后勤成本高昂，我们努力消除对这些标记的需求。在我们的机构，我们开发了一种手持式激光条纹三角测量设备，用于在手术定位时捕捉患者头部的表面轮廓。解剖表面配准算法依赖于这样的假设：患者的解剖结构与从所采用的成像模态构建的患者三维模型具有相同的几何形状。在患者成像并被放置在手术室的梅菲尔德头架中的时间间隔内，头部皮肤在针孔处隆起，并且颅骨固定设备本身会对图像采集激光产生光学干扰。我们开发了一种软件，在计算配准时拒绝属于已知几何形状物体的点。在激光扫描单元的开发过程中，我们获取了13名患者和2具尸体的表面轮廓。初步分析表明，这种自动拒绝点的方法在所有情况下都改善了配准，但并未超过基准标记方法的准确性。仅去除属于违规器械的点。由夹具和器械引起的皮肤隆起仍保留在数据中。我们预计，仔细去除这些皮肤隆起中的点将产生至少与基准标记方法准确性相匹配的配准结果。
