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Titlebook: Information Processing in Medical Imaging; 24th International C Sebastien Ourselin,Daniel C. Alexander,M. Jorge Ca Conference proceedings 2

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發(fā)表于 2025-3-25 04:08:09 | 只看該作者
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發(fā)表于 2025-3-25 08:17:50 | 只看該作者
Template-Based Multimodal Joint Generative Model of Brain Dataies. These models can then be used to describe expected intensities in an unseen image modalities given one or multiple observations, or to detect deviations (e.g. pathology) from the expected intensity patterns. In this work, we propose a template-based multi-modal generative mixture-model of imagi
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發(fā)表于 2025-3-25 15:31:04 | 只看該作者
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發(fā)表于 2025-3-26 01:03:34 | 只看該作者
Accelerated High Spatial Resolution Diffusion-Weighted Imagingntly been proposed to increase the spatial resolution in diffusion weighted imaging (DWI), providing a theoretical 8x acceleration at equal signal-to-noise ratio (SNR) compared to conventional dense k-space sampling. However, in most works, each DW image is reconstructed separately and the fact that
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發(fā)表于 2025-3-26 07:42:06 | 只看該作者
Joint Spectral Decomposition for the Parcellation of the Human Cerebral Cortex Using Resting-State fhole-brain connectivity analysis, a critical stage is the computation of a set of network nodes that can effectively represent cortical regions. To address this problem, we present a robust cerebral cortex parcellation method based on spectral graph theory and resting-state fMRI correlations that ge
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發(fā)表于 2025-3-26 11:25:08 | 只看該作者
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發(fā)表于 2025-3-26 13:14:04 | 只看該作者
Bootstrapped Permutation Test for Multiresponse Inference on Brain Behavior Associations associations between brain and behavior largely analyze each behavioral measure in isolation. To jointly model multiple behavioral scores, sparse multiresponse regression (SMR) is often used. However, directly applying SMR without statistically controlling for false positives could result in many s
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發(fā)表于 2025-3-26 19:03:37 | 只看該作者
Controlling False Discovery Rate in Signal Space for Transformation-Invariant Thresholding of Statisalse discovery rate (FDR) criterion was introduced to the neuroimaging community a decade ago, various improvements have been proposed. However, a highly desirable feature, transformation invariance, has not been adequately addressed, especially for voxel-based FDR. Thresholding applied after spatia
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