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Transfer learning in magnetic resonance brain imaging: A systematic review
(1) Background: Transfer learning refers to machine learning techniques that focus on
acquiring knowledge from related tasks to improve generalization in the tasks of interest. In …
acquiring knowledge from related tasks to improve generalization in the tasks of interest. In …
A survey of machine unlearning
Introduction Brain medical image segmentation is a critical task in medical image
processing, playing a significant role in the prediction and diagnosis of diseases such as …
processing, playing a significant role in the prediction and diagnosis of diseases such as …
Image-encoded biological and non-biological variables may be used as shortcuts in deep learning models trained on multisite neuroimaging data
Objective This work investigates if deep learning (DL) models can classify originating site
locations directly from magnetic resonance imaging (MRI) scans with and without correction …
locations directly from magnetic resonance imaging (MRI) scans with and without correction …
Improved brain age estimation with slice-based set networks
U Gupta, PK Lam, G Ver Steeg… - 2021 IEEE 18th …, 2021 - ieeexplore.ieee.org
Deep Learning for neuroimaging data is a promising but challenging direction. The high
dimensionality of 3D MRI scans makes this endeavor compute and data-intensive. Most …
dimensionality of 3D MRI scans makes this endeavor compute and data-intensive. Most …