Titlebook: Medical Image Computing and Computer-Assisted Intervention - MICCAI 2008; 11th International C Dimitris Metaxas,Leon Axel,Gábor Székely Con

现代

PATRI

A Distributed Spatio-temporal EEG/MEG Inverse Solverhose obtained through dipole fitting, but without the need to specify the number of dipole sources in advance. Furthermore, the ℓ.ℓ.-norm solver achieves fewer false positives and a better representation of the source locations than the conventional ℓ. minimum-norm estimates.

flammable

A Bayesian Approach for Liver Analysis: Algorithm and Validation Studynd second databases, and a total score of 67.87 for the second database. These results suggest that our method is accurate, efficient, and robust to seed selection compared to manually generated ground truth segmentation and to other semi-automatic segmentation methods.

Asperity

AND

archenemy

Prostate Cancer Probability Maps Based on Ultrasound RF Time Series and SVM Classifiersacted from RF time series are significantly more accurate and sensitive compared to two other established categories of ultrasound-based tissue typing methods. The method results in an area under ROC curve of 0.95 in 10-fold cross-validation.

ANTH

Streamline Flows for White Matter Fibre Pathway Segmentation in Diffusion MRIed methods, and allows multiple tracts to pass through the same voxels. We illustrate the approach with a segmentation of the corpus callosum and one of the cortico-spinal tract, with each example seeded at a single voxel.

Pruritus

atopic-rhinitis

On Computing the Underlying Fiber Directions from the Diffusion Orientation Distribution Functionvels. We also propose the use of the principal curvatures of the graph of the ODF function as a measure of the degree of diffusion anisotropy in that direction. We present simulated results illustrating the relationship between the mean principal curvature, measured at the maxima, and the fractional anisotropy of the underlying diffusion tensor.

征税

New Algorithms to Map Asymmetries of 3D Surfacestion studies. We show these two algorithms to be mathematically well-grounded, and provide some validation experiments. Then we propose a pipeline for the statistical evaluation of local asymmetries within and between populations. Finally we present some results on real data.