Transfer learning in magnetic resonance brain imaging: A systematic review

JM Valverde, V Imani, A Abdollahzadeh, R De Feo… - Journal of …, 2021 - mdpi.com
(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 …

A survey of machine unlearning

TT Nguyen, TT Huynh, Z Ren, PL Nguyen… - ar**, Y Zufang… - Frontiers in …, 2024 - frontiersin.org
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 …

Image-encoded biological and non-biological variables may be used as shortcuts in deep learning models trained on multisite neuroimaging data

R Souza, M Wilms, M Camacho, GB Pike… - Journal of the …, 2023 - academic.oup.com
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 …

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 …