Titlebook: Machine Learning in Medical Imaging; 4th International Wo Guorong Wu,Daoqiang Zhang,Fei Wang Conference proceedings 2013 Springer Internati

阻塞

crease

fMRI Analysis with Sparse Weisfeiler-Lehman Graph Statistics, propose to exploit the inherent spatial structure of the brain to improve the prediction performance of fMRI analysis. We do so in an exploratory fashion by representing the fMRI data by graphs. We use the Weisfeiler-Lehman algorithm to efficiently compute subtree features of the graphs. These feat

性上癮

Patch-Based Segmentation without Registration: Application to Knee MRI,spondence means that the segmentation results can be affected by any registration errors which occur, particularly if there is a high degree of anatomical variability. This paper presents a novel multi-resolution patch-based segmentation framework which is able to work on images without requiring re

Kidney-Failure

Virtues

殺菌劑

Metric Space Structures for Computational Anatomy,air was measured using large deformation diffeomorphic metric mapping (LDDMM). Manifold learning approaches were applied to seek a low-dimensional embedding in the high- dimensional shape space, in which inference between healthy control and disease groups can be done using standard classification a

外科醫(yī)生

使成核

Temporally Dynamic Resting-State Functional Connectivity Networks for Early MCI Identification,used by neural interactions that may happen within the scan duration. Multiple functional connectivity networks can be estimated from R-fMRI time series to effectively capture subtle yet short neural connectivity changes induced by disease pathologies. To effectively extract the temporally dynamic i

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引水渠

978-3-319-02266-6Springer International Publishing Switzerland 2013