Infant head and brain segmentation from magnetic resonance images using fusion-based deep learning strategies
Helena R. Torres,
Bruno Oliveira,
Pedro Morais
et al.
Abstract:Magnetic resonance (MR) imaging is widely used for assessing infant head and brain development and for diagnosing pathologies. The main goal of this work is the development of a segmentation framework to create patient-specific head and brain anatomical models from MR images for clinical evaluation. The proposed strategy consists of a fusion-based Deep Learning (DL) approach that combines the information of different image sequences within the MR acquisition protocol, including the axial T1w, sagittal T1w, and… Show more
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