The proposed simulated field maps facilitate susceptibility artefact reduction near the resection. Accurate air-tissue segmentation is key to achieving accurate simulation. The proposed simulation approach is adaptable to different iMRI and neurosurgical applications.
Abstract. Intraoperative MRI is a powerful modality for acquiring structural and functional images of the brain to enable precise imageguided neurosurgery. In this paper, we propose a novel method for simulating main magnetic field inhomogeneity maps during intraoperative MRI-guided neurosurgery. Our method relies on an air-tissue segmentation of intraoperative patient specific data, which is used as an input to a subsequent field simulation step. The generated simulation can then be used to enhance the precision of image-guidance. We report results of our method on 12 patient datasets acquired during image-guided neurosurgery for anterior lobe resection for surgical management of focal temporal lobe epilepsy. We find a close agreement between the field inhomogeneity maps acquired as part of the imaging protocol and the simulated field inhomogeneity maps generated by the proposed method.
Abstract. Image-guided neurosurgery involves the display of MRIbased preoperative plans in an intraoperative reference frame. Interventional MRI (iMRI) can serve as a reference for non-rigid registration based propagation of preoperative MRI. Structural MRI images exhibit spatially varying intensity relationships, which can be captured by a local similarity measure such as the local normalized correlation coefficient (LNCC). However, LNCC weights local neighborhoods using a static spatial kernel and includes voxels from beyond a tissue or resection boundary in a neighborhood centered inside the boundary. We modify LNCC to use locally adaptive weighting inspired by bilateral filtering and evaluate it extensively in a numerical phantom study, a clinical iMRI study and a segmentation propagation study. The modified measure enables increased registration accuracy near tissue and resection boundaries.
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