Hamadeh A, Lavallee S, Cinquin P
TIMC UMR 5525 IMAG, Institut Albert Bonniot, La Tronche, France.
Comput Aided Surg. 1998;3(1):11-9. doi: 10.1002/(SICI)1097-0150(1998)3:1<11::AID-IGS2>3.0.CO;2-O.
The registration of 3-dimensional (3-D) anatomical surfaces to sensor data such as intraoperative fluoroscopy is one of the basic problems in computer integrated surgery. The main objective is to find the relationship between 3-D preoperative computed tomographic images and a pair of intraoperative fluoroscopic images. Consequently, surgical navigation devices can use this relationship to provide improved surgical guidance. The proposed registration strategy presents a noninvasive anatomy-based (frameless) method for registration. In this article, we propose a cooperative approach between registration and contour segmentation on fluoroscopy. This approach is based on the duality between registration and segmentation in a model-based vision system. It associates a likelihood value to each pixel that corresponds to the probability that the pixel belongs to the contour of the object of interest. The registration is then achieved between backprojection lines stemming from likely contour pixels and the 3-D surface model of the object of interest. Then, in order to take into account the internal contour points extracted by the cooperative approach, we propose a new line to surface distance computation algorithm to be used during the data to model distance minimization step. Finally, we present the obtained results that demonstrate the validity of the proposed approach in carrying out accurate 3-D and 2-D registration.
将三维（3-D）解剖表面与术中透视等传感器数据进行配准是计算机集成手术中的基本问题之一。主要目标是找到术前三维计算机断层扫描图像与一对术中透视图像之间的关系。因此，手术导航设备可以利用这种关系来提供更好的手术指导。所提出的配准策略提出了一种基于解剖结构的非侵入性（无框架）配准方法。在本文中，我们提出了一种在透视图像上进行配准与轮廓分割的协同方法。这种方法基于基于模型的视觉系统中配准与分割之间的对偶性。它为每个像素赋予一个似然值，该似然值对应于该像素属于感兴趣对象轮廓的概率。然后在源自可能轮廓像素的反投影线与感兴趣对象的三维表面模型之间实现配准。接着，为了考虑通过协同方法提取的内部轮廓点，我们提出了一种新的线到表面距离计算算法，用于在数据到模型距离最小化步骤中使用。最后，我们展示了所获得的结果，这些结果证明了所提出方法在进行精确的三维和二维配准方面的有效性。
