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Quantitative magnetic resonance analysis often requires accurate, robust, and reliable automatic extraction of brain structures. Volume and shape of these anatomical structures are useful for pathology detection and population comparison. However, the high inter-subject variability and the modifications caused by pathology make automatic segmentation very challenging. A novel patch-based method using expert manual segmentations as priors has been proposed to achieve this task. Inspired by recent works in image denoising and label fusion segmentation, this new method has been adapted to segmentation of complex structures such as hippocampus and to brain extraction.

Anatomical Brain Structure Segmentation

Brain Extraction