Int J Comput Assist Radiol Surg - Brain-shift compensation by non-rigid registration of intra-operative ultrasound images with preoperative MR images based on residual complexity.

Tópicos

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Resumo

RPOSE: 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.

Resumo Limpo

rpose compens brain shift often necessari imageguid neurosurgeri requir registr intraop ultrasound us imag preoper magnet reson imag mri new imag similar measur base residu complex rc overcom challeng registr intraop us preoper mr imag develop testedmethod new twostag method base match echogen structur sulci achiev optim residu complex valu wavelet domain ultrasound imag probabilist map mr imag propos method compromis featurebas intensitybas approach evalu perform use special design brain phantom vivo patient data setresult result phantom data set registr confirm propos object function outperform accuraci adapt rc multimod case mean fiduci registr error reach mm method appli phantom clinic data set respectivelyconclus improv object function base rc wavelet domain enabl accur nonrigid multimod us mri imag registr robust nois technolog promis compens intraop brain shift neurosurgeri

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