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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

Koutouzi, Giasemi; Nasihatkton, Behrooz; Danielak-Nowak, Monika; Leonhardt, Henrik; Falkenberg, Mårten and Kahl, Fredrik LU (2018) In BMC Medical Imaging 18(1).
Abstract

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... (More)

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.

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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Aortic aneurysm, Cone-beam CT, Feature-based registration, Image registration, Intensity-based registration
in
BMC Medical Imaging
volume
18
issue
1
publisher
BioMed Central
external identifiers
  • scopus:85056277132
ISSN
1471-2342
DOI
10.1186/s12880-018-0285-1
language
English
LU publication?
yes
id
be456ec9-0d71-431f-9c9e-f094f49a4581
date added to LUP
2018-11-21 15:09:33
date last changed
2019-05-02 08:18:42
@article{be456ec9-0d71-431f-9c9e-f094f49a4581,
  abstract     = {<p>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&lt;0.001). Conclusion: A feature-based algorithm for 3D image registration is presented.</p>},
  articleno    = {42},
  author       = {Koutouzi, Giasemi and Nasihatkton, Behrooz and Danielak-Nowak, Monika and Leonhardt, Henrik and Falkenberg, Mårten and Kahl, Fredrik},
  issn         = {1471-2342},
  keyword      = {Aortic aneurysm,Cone-beam CT,Feature-based registration,Image registration,Intensity-based registration},
  language     = {eng},
  month        = {11},
  number       = {1},
  publisher    = {BioMed Central},
  series       = {BMC Medical Imaging},
  title        = {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},
  url          = {http://dx.doi.org/10.1186/s12880-018-0285-1},
  volume       = {18},
  year         = {2018},
}