TAF-Net adaptively fuses longitudinal structural MRI via a temporal gate to achieve top performance in 3-year MCI-to-AD conversion prediction on ADNI using only MRI.
A parameter- efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer’s disease.NeuroImage, 189:276–287, 2019
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End-Net, a multiscale CNN with inception modules, claims superior accuracy on four-class neurological disorder MRI classification and includes online deployment.
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Adaptive Temporal Gating of Longitudinal Magnetic Resonance Imaging for Alzheimer's Prediction
TAF-Net adaptively fuses longitudinal structural MRI via a temporal gate to achieve top performance in 3-year MCI-to-AD conversion prediction on ADNI using only MRI.
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A Deep Multiscale Neural Network for Accurate Neurological Disorder Detection from MRI Scans and Real-Time Web Deployment
End-Net, a multiscale CNN with inception modules, claims superior accuracy on four-class neurological disorder MRI classification and includes online deployment.