Title :
Gradient-based 2-D/3-D rigid registration of fluoroscopic X-ray to CT
Author :
Livyatan, Harel ; Yaniv, Ziv ; Joskowicz, Leo
Author_Institution :
Sch. of Eng. & Comput. Sci., Hebrew Univ., Jerusalem, Israel
Abstract :
We present a gradient-based method for rigid registration of a patient preoperative computed tomography (CT) to its intraoperative situation with a few fluoroscopic X-ray images obtained with a tracked C-arm. The method is noninvasive, anatomy-based, requires simple user interaction, and includes validation. It is generic and easily customizable for a variety of routine clinical uses in orthopaedic surgery. Gradient-based registration consists of three steps: 1) initial pose estimation; 2) coarse geometry-based registration on bone contours, and; 3) fine gradient projection registration (GPR) on edge pixels. It optimizes speed, accuracy, and robustness. Its novelty resides in using volume gradients to eliminate outliers and foreign objects in the fluoroscopic X-ray images, in speeding up computation, and in achieving higher accuracy. It overcomes the drawbacks of intensity-based methods, which are slow and have a limited convergence range, and of geometry-based methods, which depend on the image segmentation quality. Our simulated, in vitro, and cadaver experiments on a human pelvis CT, dry vertebra, dry femur, fresh lamb hip, and human pelvis under realistic conditions show a mean 0.5-1.7 mm (0.5-2.6 mm maximum) target registration accuracy.
Keywords :
bone; computerised tomography; diagnostic radiography; gradient methods; image registration; medical image processing; orthopaedics; 0.5 to 2.6 mm; CT; bone contours; coarse geometry-based registration; computed tomography; dry femur; dry vertebra; edge pixels; fine gradient projection registration; fluoroscopic X-ray images; fresh lamb hip; gradient-based 2-D rigid image registration; gradient-based 3-D rigid image registration; human pelvis; initial pose estimation; orthopaedic surgery; tracked C-arm; Bones; Computed tomography; Convergence; Ground penetrating radar; Humans; Image segmentation; Orthopedic surgery; Pelvis; Robustness; X-ray imaging; Algorithms; Animals; Cadaver; Femur; Fluoroscopy; Hip Joint; Humans; Imaging, Three-Dimensional; Intraoperative Care; Pelvis; Preoperative Care; Radiographic Image Enhancement; Radiographic Image Interpretation, Computer-Assisted; Reproducibility of Results; Sensitivity and Specificity; Sheep; Subtraction Technique; Surgery, Computer-Assisted; Tomography, X-Ray Computed;
Journal_Title :
Medical Imaging, IEEE Transactions on
DOI :
10.1109/TMI.2003.819288