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Region-based U-net for accelerated training and enhanced precision in deep brain segmentation
Segmentation of brain structures on MRI is the primary step for further quantitative analysis of brain diseases.
Translating the future: Image-to-image translation for the prediction of future brain metabolism
In conclusion, both the I2I network and the linear model could offer valuable prognostic insights, guiding early intervention strategies to preemptively address anticipated declines in brain metabolism and potentially to monitor treatment effects.
Unsupervised brain lesion segmentation from MRI using a convolutional autoencoder
Lesions that appear hyperintense in both Fluid Attenuated Inversion Recovery (FLAIR) and T2-weighted magnetic resonance images (MRIs) of the human brain are common in the brains of the elderly population and may be caused by ischemia or demyelination.
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