Titlebook: Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015; 18th International C Nassir Navab,Joachim Hornegger,Alejandro Fr

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书目名称Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015影响因子(影响力)




书目名称Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015影响因子(影响力)学科排名




书目名称Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015网络公开度




书目名称Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015网络公开度学科排名




书目名称Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015被引频次




书目名称Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015被引频次学科排名




书目名称Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015年度引用




书目名称Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015年度引用学科排名




书目名称Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015读者反馈




书目名称Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015读者反馈学科排名

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Novel Single and Multiple Shell Uniform Sampling Schemes for Diffusion MRI Using Spherical Codeson single or multiple shells in q-space. The samples in different shells are typically distributed uniformly, because they should be invariant to the orientation of structures within tissue, or the laboratory coordinate frame. The Electrostatic Energy Minimization (EEM) method, originally proposed f

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q-Space Deep Learning for Twelve-Fold Shorter and Model-Free Diffusion MRI Scans of partly redundant input data, which requires long acquisition time. This leads to high scan costs and makes advanced diffusion models such as diffusion kurtosis imaging (DKI) and neurite orientation dispersion and density imaging (NODDI) inapplicable for children and adults who are uncooperative,

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A Machine Learning Based Approach to Fiber Tractography Using Classifier Votingt tracks fiber pathways based on a random forest classification and voting process, guiding each step of the streamline progression by directly processing raw signal intensities. We evaluated our approach quantitatively and qualitatively using phantom and . data. The presented machine learning based

JECT

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An Iterated Complex Matrix Approach for Simulation and Analysis of Diffusion MRI Processes of spin particles in the presence of a magnetic field is simulated by an iterated complex matrix multiplication approach. The approach is based on first principles and provides a flexible, transparent and fast simulation tool. The experiments carried out reveals fundamental features of the dMRI pro

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