AI Article Synopsis
- Intraoperative ultrasound (iUS) combined with navigation systems and preoperative MRI helps surgeons accurately identify tumor margins during surgery.
- Two different segmentation methods, a semi-automatic technique and two registration-based methods, were tested to extract brain tumors from 3D-iUS data.
- The semi-automatic method outperformed the other techniques, especially for detecting metastasis, achieving higher similarity indices and lower contour mean distances in the results.
Article Abstract
Background: Intraoperative ultrasound (iUS), using a navigation system and preoperative magnetic resonance imaging (pMRI), supports the surgeon intraoperatively in identifying tumour margins. Therefore, visual tumour enhancement can be supported by efficient segmentation methods.
Methods: A semi-automatic and two registration-based segmentation methods are evaluated to extract brain tumours from 3D-iUS data. The registration-based methods estimated the brain deformation after craniotomy based on pMRI and 3D-iUS data. Both approaches use the normalised gradient field and linear correlation of linear combinations metrics. Proposed methods were evaluated on 66 B-mode and contrast-mode 3D-iUS data with metastasis and glioblastoma.
Results: The semi-automatic segmentation achieved superior results with dice similarity index (DSI) values between [85.34, 86.79]% and contour mean distance values between [1.05, 1.11] mm for both modalities and tumour classes.
Conclusions: Better segmentation results were obtained for metastasis detection than glioblastoma, preferring 3D-intraoperative B-mode over 3D-intraoperative contrast-mode.
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| http://dx.doi.org/10.1002/rcs.2320 | DOI Listing |
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