Computational biomechanics for image-guided neurosurgery

我们的研究结果将显著提高影像引导的脑肿瘤神经外科手术的疗效和效率。通过稀疏术中核磁共振获得的术中患者大脑结构的可视化，与高分辨率的术前成像数据合并将成为可能。在目前的实践中，神经外科医生必须通过患者大脑经历的3D空间和时间变化来投射来自术前fMRI和DTI的信息，从而在精神上融合这些信息。我们建议用基于生物力学模型的计算来取代这种心理融合，这将允许可视化与患者当前大脑形状匹配的转换的术前数据。

Our results will lead to significant improvements to the efficacy and efficiency of image-guided neurosurgery for brain tumours. Visualisation of the intra-operative configuration of the patient's brain, obtained by sparse intra-operative MRI, merged with high resolution pre-operative imaging data will become possible. In current practice, the neurosurgeon must mentally fuse the information from pre-operative fMRI and DTI by projecting it through the 3D spatial and temporal changes the patient's brain has undergone. We propose to replace this mental fusion with computations based on the biomechanical model that will allow visualisation of the transformed pre-operative data matched to the current shape of the patient's brain.