Nand K Krishna, Abugharbieh Rafeef, Booth Brian G, Hamarneh Ghassan
Biomedical Signal and Image Computing Lab, University of British Columbia.
Med Image Comput Comput Assist Interv. 2011;14(Pt 2):90-7. doi: 10.1007/978-3-642-23629-7_12.
We derive herein first and second-order differential operators for detecting structure in diffusion tensor MRI (DTI). Unlike existing methods, we are able to generate full first and second-order differentials without dimensionality reduction and while respecting the underlying manifold of the data. Further, we extend corner and curvature feature detectors to DTI using our differential operators. Results using the feature detectors on diffusion tensor MR images show the ability to highlight structure within the image that existing methods cannot.
我们在此推导用于检测扩散张量磁共振成像（DTI）中结构的一阶和二阶微分算子。与现有方法不同，我们能够在不进行降维且尊重数据底层流形的情况下生成完整的一阶和二阶微分。此外，我们使用我们的微分算子将角点和曲率特征检测器扩展到DTI。在扩散张量磁共振图像上使用这些特征检测器的结果表明，其能够突出显示现有方法无法显示的图像中的结构。
