Precise and rapid whole-head segmentation from magnetic resonance images of older adults using deep learning
Developed a deep learning model that specializes in the segmentation of brain images of older adults. Many current models are trained on younger adults and may not apply to an older population.
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Principal Investigator: Dr. Ruogu Fang
Department: Biomedical Engineering
Years with Project: 1 year
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Responsibilities
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Wrote a program to visualize 2D slices of segmentations, with the ability to color different tissue types different colors.
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Wrote a program to calculate the accuracy of segmentations produced by the model.
Broader Impact
Brain segmentations can help with a variety of treatments, including non-invasive brain stimulation. These treatments are often used in older adults for age-related disorders. By creating a model specific to the older population, these segmentations and treatments can be more accurate.