Performance of a feature-based algorithm for 3D-3D registration of CT angiography to cone-beam CT for endovascular repair of complex abdominal aortic aneurysms
Journal article, 2018

Background: A crucial step in image fusion for intraoperative guidance during endovascular procedures is the registration of preoperative computed tomography angiography (CTA) with intraoperative Cone Beam CT (CBCT). Automatic tools for image registration facilitate the 3D image guidance workflow. However their performance is not always satisfactory. The aim of this study is to assess the accuracy of a new fully automatic, feature-based algorithm for 3D3D registration of CTA to CBCT. Methods: The feature-based algorithm was tested on clinical image datasets from 14 patients undergoing complex endovascular aortic repair. Deviations in Euclidian distances between vascular as well as bony landmarks were measured and compared to an intensity-based, normalized mutual information algorithm. Results: The results for the feature-based algorithm showed that the median 3D registration error between the anatomical landmarks of CBCT and CT images was less than 3mm. The feature-based algorithm showed significantly better accuracy compared to the intensity-based algorithm (p<0.001). Conclusion: A feature-based algorithm for 3D image registration is presented.

Cone-beam CT

Intensity-based registration

Image registration

Feature-based registration

Aortic aneurysm


Giasemi Koutouzi

University of Gothenburg

Behrooz Nasihatkton

K. N. Toosi University of Technology

Monika Danielak-Nowak

University of Gothenburg

Henrik Leonhardt

University of Gothenburg

Mårten Falkenberg

University of Gothenburg

Fredrik Kahl

Lund University

Chalmers, Electrical Engineering, Signal Processing and Biomedical Engineering

BMC Medical Imaging

14712342 (eISSN)

Vol. 18 1 42

Subject Categories

Radiology, Nuclear Medicine and Medical Imaging

Computer Vision and Robotics (Autonomous Systems)

Medical Image Processing





More information

Latest update