Titlebook: Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014; 17th International C Polina Golland,Nobuhiko Hata,Robert Howe Con

TATE

Functionally Driven Brain Networks Using Multi-layer Graph Clustering our technique provides subject-specific factors designed to characterize and quantify the degree of intra- and inter- connectivity between hubs, thereby providing a representation that is amenable to group level statistical analyses. We demonstrate the utility of the technique by creating a populat

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Single-Subject Structural Networks with Closed-Form Rotation Invariant Matching Improve Power in Devin matures. The derived graph metrics demonstrate a four-fold increase in power for detecting age as compared to cortical thickness. This proof of concept study indicates that the proposed metric may be useful in identifying biologically relevant cortical patterns.

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,-Relaxometry for Myelin Water Fraction Extraction Using Wald Distribution and Extended Phase Grapht the distribution of the relative amount of water in between myelin sheets, tissue water, and cerebrospinal fluid. The parameters of the model are estimated using the variable projection method and are used to extract the MWF at each voxel. In addition, we use Extended Phase Graph (EPG) method to c

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歪曲道理

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Simulating Neurodegeneration through Longitudinal Population Analysis of Structural and Diffusion Wemages. Additionally, simulated maps of volume change are generated, which can be compared to maps estimated from real longitudinal data. The results indicate that the proposed simulator reproduces realistic patient-specific patterns of longitudinal brain change for the given populations.

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The 4D Hyperspherical Diffusion Wavelet: A New Method for the Detection of Localized Anatomical Varirence of highly localized anatomical changes, which we demonstrate in the first-ever developmental study on the hyoid bone investigating gender and age effects. We also show that the hyperspherical wavelet successfully picks up group-wise differences that are barely detectable using SPHARM.

职业

Bayesian Principal Geodesic Analysis in Diffeomorphic Image Registrationatabase of magnetic resonance images. We show that the automatically selected latent dimensions from our model are able to reconstruct unseen brain images with lower error than equivalent linear principal components analysis (LPCA) models in the image space, and it also outperforms tangent space PCA (TPCA) models in the diffeomorphism setting.

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Low-Rank to the Rescue – Atlas-Based Analyses in the Presence of Pathologiesinput MRIs, the low-rank components are then re-computed based on those registrations, and the process is then iteratively repeated. Preliminary evaluations are conducted using the brain tumor segmentation challenge data (BRATS ’12).