Difference between revisions of "Projects:BayesianMRSegmentation"
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= Model-Based Segmentation of Hippocampal Subfields = | = Model-Based Segmentation of Hippocampal Subfields = | ||
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| + | Recent developments in MR data acquisition technology are starting to yield images that show anatomical features of the hippocampal formation at an unprecedented level of detail, providing the basis for hippocampal subfield measurement. Because of the role of the hippocampus in human memory and its implication in a variety of disorders and conditions, the ability to reliably and efficiently quantify its subfields through in vivo neuroimaging is of great interest to both basic neuroscience and clinical research. The aim of this project is to develop and validate a fully-automated method for segmenting the hippocampal subfields in ultra-high resolution | ||
| + | MRI data. | ||
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Revision as of 20:33, 16 May 2008
Home < Projects:BayesianMRSegmentationBack to NA-MIC Collaborations, MIT Algorithms
Model-Based Segmentation of Hippocampal Subfields
Recent developments in MR data acquisition technology are starting to yield images that show anatomical features of the hippocampal formation at an unprecedented level of detail, providing the basis for hippocampal subfield measurement. Because of the role of the hippocampus in human memory and its implication in a variety of disorders and conditions, the ability to reliably and efficiently quantify its subfields through in vivo neuroimaging is of great interest to both basic neuroscience and clinical research. The aim of this project is to develop and validate a fully-automated method for segmenting the hippocampal subfields in ultra-high resolution MRI data.
Key Investigators
- MIT Algorithms: Koen Van Leemput, Polina Golland
