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3D–2D registration in endovascular image-guided surgery: evaluation of state-of-the-art methods on cerebral angiograms

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Image guidance for minimally invasive surgery is based on spatial co-registration and fusion of 3D pre-interventional images and treatment plans with the 2D live intra-interventional images. The spatial co-registration or 3D–2D registration is the key enabling technology; however, the performance of state-of-the-art automated methods is rather unclear as they have not been assessed under the same test conditions. Herein we perform a quantitative and comparative evaluation of ten state-of-the-art methods for 3D–2D registration on a public dataset of clinical angiograms.

Methods

Image database consisted of 3D and 2D angiograms of 25 patients undergoing treatment for cerebral aneurysms or arteriovenous malformations. On each of the datasets, highly accurate “gold-standard” registrations of 3D and 2D images were established based on patient-attached fiducial markers. The database was used to rigorously evaluate ten state-of-the-art 3D–2D registration methods, namely two intensity-, two gradient-, three feature-based and three hybrid methods, both for registration of 3D pre-interventional image to monoplane or biplane 2D images.

Results

Intensity-based methods were most accurate in all tests (0.3 mm). One of the hybrid methods was most robust with 98.75% of successful registrations (SR) and capture range of 18 mm for registrations of 3D to biplane 2D angiograms. In general, registration accuracy was similar whether registration of 3D image was performed onto mono- or biplanar 2D images; however, the SR was substantially lower in case of 3D to monoplane 2D registration. Two feature-based and two hybrid methods had clinically feasible execution times in the order of a second.

Conclusions

Performance of methods seems to fall below expectations in terms of robustness in case of registration of 3D to monoplane 2D images, while translation into clinical image guidance systems seems readily feasible for methods that perform registration of the 3D pre-interventional image onto biplanar intra-interventional 2D images.

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Funding

This research was supported by the Slovenian Research Agency (Grants Nos. P2-0232, J2-5473, J7-6781, J2-7211 and J2-8173).

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Authors and Affiliations

  1. Cosylab, Control System Laboratory, Gerbičeva ulica 64, 1000, Ljubljana, Slovenia

    Uroš Mitrović

  2. Faculty of Electrical Engineering, University of Ljubljana, Tržaška 25, 1000, Ljubljana, Slovenia

    Boštjan Likar, Franjo Pernuš & Žiga Špiclin

  3. Sensum, Computer Vision Systems, Tehnološki park 21, 1000, Ljubljana, Slovenia

    Boštjan Likar & Franjo Pernuš

Authors
  1. Uroš Mitrović
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  2. Boštjan Likar
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  3. Franjo Pernuš
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  4. Žiga Špiclin
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Correspondence to Žiga Špiclin.

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Mitrović, U., Likar, B., Pernuš, F. et al. 3D–2D registration in endovascular image-guided surgery: evaluation of state-of-the-art methods on cerebral angiograms. Int J CARS 13, 193–202 (2018). https://doi.org/10.1007/s11548-017-1678-2

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  • DOI: https://doi.org/10.1007/s11548-017-1678-2

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