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Spatial alignment of functional magnetic resonance images (fMRI) of different subjects is a necessary precursor to improve functional consistency across subjects for group analysis in fMRI studies. Traditional structural MRI (sMRI) based registration methods cannot achieve accurate inter-subject functional consistency in that functional units are not necessarily located relative to anatomical structures...
We propose a groupwise image registration method using sparse coding and graph theoretic techniques. A sparse coding method is used to estimate image similarity measures among images to registered, yielding asymmetric, groupwise image similarity measures for each image to other images in the group. Based on the asymmetric groupwise image similarity measures among different images, a directed graph...
For medical image segmentation, multi-atlas based segmentation methods have attracted great attention recently. Within the multi-atlas segmentation framework, labels of all atlases are propagated to the target image by means of image registration and then fused to achieve segmentation of the target image. While most multi-atlas based segmentation methods focus on developing effective label fusion...
The inter-subject alignment is an important precursor to improve consistency across subjects for statistical group analysis in functional magnetic resonance imaging (fMRI) studies. To overcome the limitations of existing techniques and further improve inter-subject functional consistency, we propose a novel image registration method for fMRI data based on features of multi-range functional connectivity...
A number of neurological diseases are associated with structural and functional alterations in the brain. This paper presents a method of using both structural and functional MR images for brain disease diagnosis, by machine learning and high-dimensional template warping. First, a high-dimensional template warping technique is used to compute morphological and functional representations for each individual...
A number of neurological diseases are associated with structural and functional alterations in the brain. This paper presents a method of using both structural and functional MR images for brain disease diagnosis, by machine learning and high-dimensional template warping. First, a high-dimensional template warping technique is used to compute morphological and functional representations for each individual...
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