3-D/2-D registration of CT and MR to X-ray images

Abstract

A crucial part of image-guided therapy is registration of preoperative and intraoperative images, by which the precise position and orientation of the patient's anatomy is determined in three dimensions. This paper presents a novel approach to register three-dimensional (3-D) computed tomography (CT) or magnetic resonance (MR) images to one or more two-dimensional (2-D) X-ray images. The registration is based solely on the information present in 2-D and 3-D images. It does not require fiducial markers, intraoperative X-ray image segmentation, or timely construction of digitally reconstructed radiographs. The originality of the approach is in using normals to bone surfaces, preoperatively defined in 3-D MR or CT data, and gradients of intraoperative X-ray images at locations defined by the X-ray source and 3-D surface points. The registration is concerned with finding the rigid transformation of a CT or MR volume, which provides the best match between surface normals and back projected gradients, considering their amplitudes and orientations. We have thoroughly validated our registration method by using MR, CT, and X-ray images of a cadaveric lumbar spine phantom for which "gold standard" registration was established by means of fiducial markers, and its accuracy assessed by target registration error. Volumes of interest, containing single vertebrae L1-L5, were registered to different pairs of X-ray images from different starting positions, chosen randomly and uniformly around the "gold standard" position. CT/X-ray (MR/ X-ray) registration, which is fast, was successful in more than 91% (82% except for L1) of trials if started from the "gold standard" translated or rotated for less than 6 mm or 17 degrees (3 mm or 8.6 degrees), respectively. Root-mean-square target registration errors were below 0.5 mm for the CT to X-ray registration and below 1.4 mm for MR to X-ray registration.

Vision Based Robotic Navigation: Application to Orthopedic Surgery

“…These methodologies can be grouped as feature based registration techniques (Besl and McKay. 1992;Taylor, Mittelstadt et al 1994;Lavallee, Szeliski et al 1995;Livyatan, Yaniv et al 2003;Tomaževic, Likar et al 2003) or as intensity based registration techniques (Penney, Batchelor et al 2001;Zollei, Grimson et al 2001;Rohlfing and Maurer 2002). Feature based approaches rely on the presence and identification of natural landmarks in the input datasets in order to determine the best alignment.…”

“…Surface based (Besl and McKay. 1992;Lavallee, Szeliski et al 1995;Livyatan, Yaniv et al 2003;Tomaževic, Likar et al 2003) feature registration approaches utilize the outer surfaces of an object of interest (extracted from a 3D model), and contours that outline the object on one or more 2D images. Registration is concerned with finding the object pose that minimizes the distance between surface and the contour.…”

“…Another methodology is to project 3D surface points onto the 2D plane and then attempt to minimize the distance between the contour of the projected image and the initial 2D contour. The work done by (Lavallee, Szeliski et al 1995;Livyatan, Yaniv et al 2003;Tomaževic, Likar et al 2003) has presented another methodology where projections of the volumetric data gradients are computed and compared with X-ray image gradients. The volumetric data pose is adjusted to minimize this gradient difference.…”

“…Literature work that conduct tracking of fractured bone segments through intra-operative 2D-3D registration can be is seen in (Joskowicz L, Milgrom C et al 1998;Gamage, Xie et al 2008). Intra-operative pose estimation techniques could further be used during spinal orthopedic procedures such as reinforcement of falling vertebra and pedicle screw placement (Penny 1999;Tomaževic, Likar et al 2003). Furthermore, in hip arthroplasty, the positioning and implanting of the acetabular cup into the pelvic bone can also be aided through intra-operative pose estimation (LaRose, Cassenti et al 2000;Hüfner, Meller et al 2005).…”

Technology preview: X‐ray fused with magnetic resonance during invasive cardiovascular procedures

“…Volumetric or tomographic images acquired using MRI or CT need to be transformed before combining with 2D projections acquired using X-ray fluoroscopy. Approaches to image registration include (a) assuming that a patient is immobilized on a table that is moved and tracked between imaging modalities [7]; (b) attaching common reference points (known as fiducial markers) to the surface of the patient, and using the correspondence of those fiducial markers to warp the rest of the images until they overlap [8]; (c) using intrisinsic fiducial markers, such as bones or vessel bifurcations [9]; (d) using automated or manual manipulation of the image similarity to make them correspond [10]. Here, we test the second technique, which is attractive because it is amenable to real-time implementation, simple, robust, not reliant on multiple radio-contrast runs, and adjustable for patient movement.…”