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International Journal of Computer Assisted Radiology and Surgery

Erschienen in:

01.05.2015 | Original Article

Brain-shift compensation by non-rigid registration of intra-operative ultrasound images with preoperative MR images based on residual complexity

verfasst von: P. Farnia, A. Ahmadian, T. Shabanian, N. D. Serej, J. Alirezaie

Erschienen in: International Journal of Computer Assisted Radiology and Surgery | Ausgabe 5/2015

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Abstract

Purpose

Compensation for brain shift is often necessary for image-guided neurosurgery, requiring registration of intra-operative ultrasound (US) images with preoperative magnetic resonance images (MRI). A new image similarity measure based on residual complexity (RC) to overcome challenges of registration of intra-operative US and preoperative MR images was developed and tested.

Method

A new two-stage method based on the matching echogenic structures such as sulci is achieved by optimizing the residual complexity value in the wavelet domain between the ultrasound image and the probabilistic map of the MR image. The proposed method is a compromise between feature-based and intensity-based approaches. Evaluation was performed using a specially designed brain phantom and an in vivo patient data set.

Result

The results of the phantom data set registration confirmed that the proposed objective function outperforms the accuracy of adapted RC for multi-modal cases by 48 %. The mean fiducial registration error reached 1.17 and 2.14 mm when the method was applied on phantom and clinical data sets, respectively.

Conclusion

This improved objective function based on RC in the wavelet domain enables accurate non-rigid multi-modal (US and MRI) image registration which is robust to noise. This technology is promising for compensation of intra-operative brain shift in neurosurgery.

Vorheriger Artikel A projected landmark method for reduction of registration error in image-guided surgery systems

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Titel: Brain-shift compensation by non-rigid registration of intra-operative ultrasound images with preoperative MR images based on residual complexity
verfasst von: P. Farnia
A. Ahmadian
T. Shabanian
N. D. Serej
J. Alirezaie
Publikationsdatum: 01.05.2015
Verlag: Springer Berlin Heidelberg
Erschienen in: International Journal of Computer Assisted Radiology and Surgery / Ausgabe 5/2015
Print ISSN: 1861-6410
Elektronische ISSN: 1861-6429
DOI: https://doi.org/10.1007/s11548-014-1098-5

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Abstract

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Conclusion

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