Titlebook: Machine Learning in Medical Imaging; Third International Fei Wang,Dinggang Shen,Kenji Suzuki Conference proceedings 2012 Springer-Verlag B

expository

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Data Driven Constraints for the SVM,ically on the human ear canal. This is particularly interesting in dynamic cases such as tissue movement or pathologies developing over time. Assuming that two observations of the same subject in different states span a vector, we hypothesise that such structure of the data contains implicit informa

enormous

Towards Improving the Accuracy of Sensorless Freehand 3D Ultrasound by Learning,external position sensor. Conventionally, in-plane motion is compensated by maximizing image correlation. Out-of-plane motion is then estimated using a calibrated model of elevational speckle decorrelation. This approach is prone to systematic error due to interactions between the effects of in-plan

Largess

A Novel 3D Joint MGRF Framework for Precise Lung Segmentation, (CT) is proposed. The CT images, Gaussian Scale Space (GSS) data generation using Gaussian Kernels (GKs), and desired maps of regions (lung and the other chest tissues) are described by a joint Markov-Gibbs Random Field (MGRF) model of independent image signals and interdependent region labels impl

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Human Age Estimation with Surface-Based Features from MRI Images,pose a novel regression model with surface-based features to estimate the human age automatically and accurately. First, individual regional surface-based features (thickness, mean curvature, Gaussian curvature and surface area) from the MRI image were extracted, which were subsequently used to cons

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自負(fù)的人

Simultaneous Registration and Segmentation by L1 Minimization,one of the images is well segmented by automated algorithm or user interaction. This image acts as an atlas for the segmentation process. For the remaining images in the set, we propose a novel L1 minimization based technique, which leverages the fact that the other image is not closely segmented bu

dry-eye

On the Creation of Generic fMRI Feature Networks Using 3-D Moment Invariants,classification, can aid the detection of groups of informative voxels that can be used to discriminate between competing stimuli. Networks of features have been long extracted univariately but recently researchers have turned to the development of multivariate techniques that also move from being pu