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Showing 1 to 13 of 13 for “"parcellation"”.

  1. Prior information for brain parcellation

    To better understand brain disease, many neuroscientists study anatomical differences between normal and diseased subjects. Frequently, they analyze medical images to locate brain structures influenced by disease. Many of these structures have weakly visible boundaries so that standard image …

    mit Repository record for Prior information for brain parcellation (opens in a new tab)

  2. Unsupervised connectivity-based cortex parcellation using the information bottleneck method

    In this dissertation, we embody an information-theoretic framework to compress and therefore cluster anatomical connectivity data that avoids many assumptions and drawbacks imposed by previous methods.

    cape-town Repository record for Unsupervised connectivity-based cortex parcellation using the information bottleneck method (opens in a new tab)

  3. Advanced Statistical Learning Methods in Image Processing

    … quantification. Third, in the brain image parcellation problem, we propose a new principal parcellation analysis for learning the relevant ROIs automatically based on white matter fiber bundles. We develop a novel framework that conducts the clustering analysis on the fibers' ending points …

    rice Repository record for Advanced Statistical Learning Methods in Image Processing (opens in a new tab)

  4. Dynamic Neural Correlates of Mental Attention Capacity

    … of resting-state functional MRI data with parcellation of individual brains into a common set of functional areas (Group Prior Individual Parcellation, GPIP) was used to determine whether dFC is 1) related to individual differences in M-capacity and 2) modulated by prior performance of a …

    york Repository record for Dynamic Neural Correlates of Mental Attention Capacity (opens in a new tab)

  5. Postmortem image analysis of the human brain to characterize Alzheimer's disease and related dementias

    … tissue segmentation and surface-based anatomical parcellation pipeline for whole cerebral hemisphere 7 tesla postmortem MRI in diseased populations. Next, by constructing a population-level postmortem ex vivo MRI template, we conduct both voxel-based and surface-based point-wise statistical …

    penn Repository record for Postmortem image analysis of the human brain to characterize Alzheimer's disease and related dementias (opens in a new tab)

  6. Learning task-optimal image registration with applications in localizing structure and function in the cerebral cortex

    … segmentation, we demonstrate improvements in parcellation of the cerebral cortex into different structural units. In this thesis, we work with spherical representations of the human cerebral cortex. Consequently, we develop a fast algorithm for registering spherical images. Application to the …

    mit Repository record for Learning task-optimal image registration with applications in localizing structure and function in the cerebral cortex (opens in a new tab)

  7. Abnormal cell patterning at the cortical gray-white matter boundary in autism spectrum disorders

    … cortical measures that rely on gray-white matter parcellation, since an indistinct transition zone could lead to a misplaced cortical boundary and errors in both thickness and volume measures.

    unr Repository record for Abnormal cell patterning at the cortical gray-white matter boundary in autism spectrum disorders (opens in a new tab)

  8. The role of modularity and integration in shaping primate pelvic girdle evolution

    … covary more closely together. The pubis-ischium parcellation is present in all examined primate phylogenetic groups (Lemuroidea, Ceboidea, Cercopithecoidea, and Hominoidea – humans excluded), suggesting that this parcellation was present in basal primates. Notably, a significant modular signal is …

    cambridge Repository record for The role of modularity and integration in shaping primate pelvic girdle evolution (opens in a new tab)

  9. INHIBITORY CONTROL AND ITS RELATION TO PERSONALITY/TEMPERAMENT, EXECUTIVE FUNCTION, AND THE BRAIN

    … subareas of the OFC and SFC, an innovative parcellation method was used. Results suggested that the temperament and executive function measures of inhibitory control did form a single factor as long as they were measured within the same modality, parent-report. In contrast, the …

    siu-theses Repository record for INHIBITORY CONTROL AND ITS RELATION TO PERSONALITY/TEMPERAMENT, EXECUTIVE FUNCTION, AND THE BRAIN (opens in a new tab)

  10. Exploring the functional organization of cerebral cortex using data from the Human Connectome Project

    … auditory, and language cortex. The cortical parcellation scheme presented here provides a comprehensive and unified map of functionally defined areas, which could replace a large set of functional localizer maps. At the end of the thesis, I outline additional ongoing projects using the HCP …

    cambridge Repository record for Exploring the functional organization of cerebral cortex using data from the Human Connectome Project (opens in a new tab)

  11. An investigation of a neuro-inflammatory profile of HIV-associated neurocognitive disorders

    … cortical regions were derived using automated parcellation of T1-weighted images acquired at 3T. Markers were correlated with neurocognitive performance and cortical thickness and surface area. Further, a prospective review of the literature was performed to determine the association between …

    cape-town Repository record for An investigation of a neuro-inflammatory profile of HIV-associated neurocognitive disorders (opens in a new tab)

  12. Anatomical and Functional Organization of Domain-General Brain Regions

    How does complex brain activity organize thought and behaviour? Theoretical proposals have long emphasized that intelligent behaviour must be supported by a flexible control system. Numerous brain imaging studies identified a domain-general or “multiple-demand” (MD) brain system co-activated …

    cambridge Repository record for Anatomical and Functional Organization of Domain-General Brain Regions (opens in a new tab)

  13. The resurgence of structure in deep neural networks

    Machine learning with deep neural networks ("deep learning") allows for learning complex features directly from raw input data, completely eliminating hand-crafted, "hard-coded" feature extraction from the learning pipeline. This has lead to state-of-the-art performance being achieved across …

    cambridge Repository record for The resurgence of structure in deep neural networks (opens in a new tab)