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
Artikel i vetenskaplig tidskrift, 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.

Aortic aneurysm

Cone-beam CT

Feature-based registration

Image registration

Intensity-based registration

Författare

Giasemi Koutouzi

Sahlgrenska akademin

Behrooz Nasihatkton

K. N. Toosi University of Technology

Monika Danielak-Nowak

Sahlgrenska akademin

Henrik Leonhardt

Sahlgrenska akademin

Mårten Falkenberg

Sahlgrenska akademin

Fredrik Kahl

Chalmers, Elektroteknik, Signalbehandling och medicinsk teknik, Digitala bildsystem och bildanalys

Lunds universitet

BMC Medical Imaging

1471-2342 (ISSN)

Vol. 18 1 42

Ämneskategorier

Radiologi och bildbehandling

Datorseende och robotik (autonoma system)

Medicinsk bildbehandling

DOI

10.1186/s12880-018-0285-1

PubMed

30409129

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Senast uppdaterat

2019-01-24