Deep learning for image enhancement and correction in magnetic resonance imaging—state-of-the-art and challenges

Z Chen, K Pawar, M Ekanayake, C Pain, S Zhong… - Journal of Digital …, 2023 - Springer
Magnetic resonance imaging (MRI) provides excellent soft-tissue contrast for clinical
diagnoses and research which underpin many recent breakthroughs in medicine and …

The lifespan human connectome project in aging: an overview

SY Bookheimer, DH Salat, M Terpstra, BM Ances… - Neuroimage, 2019 - Elsevier
Abstract The original Human Connectome Project yielded a rich data set on structural and
functional connectivity in a large sample of healthy young adults using improved methods of …

On instabilities of deep learning in image reconstruction and the potential costs of AI

V Antun, F Renna, C Poon, B Adcock… - Proceedings of the …, 2020 - National Acad Sciences
Deep learning, due to its unprecedented success in tasks such as image classification, has
emerged as a new tool in image reconstruction with potential to change the field. In this …

Image reconstruction by domain-transform manifold learning

B Zhu, JZ Liu, SF Cauley, BR Rosen, MS Rosen - Nature, 2018 - nature.com
Image reconstruction is essential for imaging applications across the physical and life
sciences, including optical and radar systems, magnetic resonance imaging, X-ray …

Extending the Human Connectome Project across ages: Imaging protocols for the Lifespan Development and Aging projects

MP Harms, LH Somerville, BM Ances, J Andersson… - Neuroimage, 2018 - Elsevier
Abstract The Human Connectome Projects in Development (HCP-D) and Aging (HCP-A) are
two large-scale brain imaging studies that will extend the recently completed HCP Young …

The difficulty of computing stable and accurate neural networks: On the barriers of deep learning and Smale's 18th problem

MJ Colbrook, V Antun… - Proceedings of the …, 2022 - National Acad Sciences
Deep learning (DL) has had unprecedented success and is now entering scientific
computing with full force. However, current DL methods typically suffer from instability, even …

Population-averaged atlas of the macroscale human structural connectome and its network topology

FC Yeh, S Panesar, D Fernandes, A Meola, M Yoshino… - Neuroimage, 2018 - Elsevier
A comprehensive map of the structural connectome in the human brain has been a coveted
resource for understanding macroscopic brain networks. Here we report an expert-vetted …

Morphometric similarity networks detect microscale cortical organization and predict inter-individual cognitive variation

J Seidlitz, F Váša, M Shinn, R Romero-Garcia… - Neuron, 2018 - cell.com
Macroscopic cortical networks are important for cognitive function, but it remains challenging
to construct anatomically plausible individual structural connectomes from human …

[HTML][HTML] What's new and what's next in diffusion MRI preprocessing

CMW Tax, M Bastiani, J Veraart, E Garyfallidis… - NeuroImage, 2022 - Elsevier
Diffusion MRI (dMRI) provides invaluable information for the study of tissue microstructure
and brain connectivity, but suffers from a range of imaging artifacts that greatly challenge the …

The Lifespan Human Connectome Project in Development: A large-scale study of brain connectivity development in 5–21 year olds

LH Somerville, SY Bookheimer, RL Buckner… - Neuroimage, 2018 - Elsevier
Recent technological and analytical progress in brain imaging has enabled the examination
of brain organization and connectivity at unprecedented levels of detail. The Human …