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Updated: Jul 14, 2026
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Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
Published on: September 25, 2019
Validation of vessel-based registration for correction of brain shift
I Reinertsen1, M Descoteaux, K Siddiqi
1Montreal Neurological Institute (MNI), McGill University, Montréal, Canada. Ingerid.Reinertsen@sintef.no
Medical Image Analysis
|May 26, 2007
Summary
This study presents a novel method to correct brain shift during neurosurgery using MR and ultrasound images. The technique accurately corrects significant brain deformations, improving surgical navigation accuracy.
Area of Science:
- Neurosurgery
- Medical Imaging
- Image-Guided Surgery
Background:
- Brain shift, a significant deformation of brain tissue, introduces substantial errors in image-guided neurosurgery.
- Accurate intraoperative navigation is crucial for successful neurosurgical interventions.
Purpose of the Study:
- To develop and validate a method for detecting and correcting brain shift using pre-operative MR and intraoperative Doppler ultrasound data.
- To improve the accuracy of image-guided neurosurgery systems by addressing brain deformation.
Main Methods:
- A novel algorithm was developed utilizing segmented vessels from both MR and ultrasound modalities.
- The iterative closest point (ICP) algorithm, modified with least trimmed squares (LTS) for outlier reduction, estimated brain deformation.
- A thin-plate spline transform was employed for non-linear registration based on the estimated deformation.
Main Results:
- Simulations showed the technique recovered 75% of deformation up to 20 mm in the region of interest.
- In phantom studies, ultrasound-based registration corrected 7.5 mm deformations to within 1.6 mm.
- MR-based registration achieved an average correction accuracy of 1.07 mm for the same deformations.
Conclusions:
- The developed method effectively detects and corrects brain shift using multimodal imaging.
- This technique has the potential to significantly enhance the precision and safety of image-guided neurosurgery.
