Anatomy-based registration of CT-scan and intraoperative X-ray images for guiding a surgical robot

• Published in: IEEE transactions on medical imaging Vol. 17; no. 5; pp. 715 - 728
• Main Authors: Gueziec, A., Kazanzides, P., Williamson, B., Taylor, R.H.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.10.1998
• Subjects: Algorithm design and analysis; Algorithms; Anatomy; Arthroplasty, Replacement, Hip; Bone and Bones - diagnostic imaging; Bones; Calibration; Computed tomography; Embedded computing; Fluoroscopy; Humans; Image Processing, Computer-Assisted; Image segmentation; Intraoperative Period; Medical robotics; Radiography; Robotics; Robots; Surgery; Surgical Procedures, Operative; Therapy, Computer-Assisted; Tomography, X-Ray Computed; X ray analysis; X-ray imaging
• ISSN: 0278-0062
• DOI: 10.1109/42.736023

Describes new methods for rigid registration of a preoperative computed tomography (CT)-scan image to a set of intraoperative X-ray fluoroscopic images, for guiding a surgical robot to its trajectory planned from CT. Our goal is to perform the registration, i.e., compute a rotation and translation of one data set with respect to the other to within a prescribed accuracy, based upon bony anatomy only, without external fiducial markers. With respect to previous approaches, the following aspects are new: (1) the authors correct the geometric distortion in fluoroscopic images and calibrate them directly with respect to the robot by affixing to it a new calibration device designed as a radiolucent rod with embedded metallic markers, and by moving the device along two planes, while radiographs are being acquired at regular intervals; (2) the registration uses an algorithm for computing the best transformation between a set of lines in three space, the (intraoperative) X-ray paths, and a set of points on the surface of the bone (imaged preoperatively), in a statistically robust fashion, using the Cayley parameterization of a rotation; and (3) to find corresponding sets of points to the X-ray paths on the surfaces, the authors' new approach consists of extracting the surface apparent contours for a given viewpoint, as a set of closed three-dimensional nonplanar curves, before registering the apparent contours to X-ray paths. Aside from algorithms, there are a number of major technical difficulties associated with engineering a clinically viable system using anatomy and image-based registration. To detect and solve them, the authors have so far conducted two experiments with the surgical robot in an operating room (OR), using CT and fluoroscopic image data of a cadaver bone, and attempting to faithfully simulate clinical conditions. Such experiments indicate that intraoperative X-ray-based registration is a promising alternative to marker-based registration for clinical use with the authors' proposed method.