Automated 3-Dimensional Computed Tomographic and Fluoroscopic Image Registration

Abstract

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.