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High Resolution Hippocampus Subfield Segmentation Using Multispectral Multiatlas Patch-Based Label Fusion

Abstract : The hippocampus is a brain structure that is involved in several cog-nitive functions such as memory and learning. It is a structure of grate interest due to its relationship to neurodegenerative processes such as the Alzheimer's disease. In this work, we propose a novel multispectral multiatlas patch-based method to automatically segment hippocampus subfields using high resolution T1-weighted and T2-weighted magnetic resonance images (MRI). The proposed method works well also on standard resolution images after superresolu-tion and consistently performs better than monospectral version. Finally, the proposed method was compared with similar state-of-the-art methods showing better results in terms of both accuracy and efficiency.
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https://hal.archives-ouvertes.fr/hal-01398769
Contributor : Pierrick Coupé <>
Submitted on : Thursday, November 17, 2016 - 4:49:47 PM
Last modification on : Tuesday, March 17, 2020 - 10:26:53 AM
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José Romero, Pierrick Coupe, José Manjón. High Resolution Hippocampus Subfield Segmentation Using Multispectral Multiatlas Patch-Based Label Fusion. Patch-Based Techniques in Medical Imaging (MICCAI), Oct 2016, Athènes, Greece. pp.117 - 124, ⟨10.1007/978-3-319-47118-1_15⟩. ⟨hal-01398769⟩

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