iBEAT V2. 0: a multisite-applicable, deep learning-based pipeline for infant cerebral cortical surface reconstruction

L Wang, Z Wu, L Chen, Y Sun, W Lin, G Li - Nature protocols, 2023 - nature.com
The human cerebral cortex undergoes dramatic and critical development during early
postnatal stages. Benefiting from advances in neuroimaging, many infant brain magnetic …

Deep learning for neuroimaging-based diagnosis and rehabilitation of autism spectrum disorder: a review

M Khodatars, A Shoeibi, D Sadeghi… - Computers in biology …, 2021 - Elsevier
Abstract Accurate diagnosis of Autism Spectrum Disorder (ASD) followed by effective
rehabilitation is essential for the management of this disorder. Artificial intelligence (AI) …

The OpenNeuro resource for sharing of neuroscience data

CJ Markiewicz, KJ Gorgolewski, F Feingold, R Blair… - Elife, 2021 - elifesciences.org
The sharing of research data is essential to ensure reproducibility and maximize the impact
of public investments in scientific research. Here, we describe OpenNeuro, a BRAIN …

Robust machine learning segmentation for large-scale analysis of heterogeneous clinical brain MRI datasets

B Billot, C Magdamo, Y Cheng… - Proceedings of the …, 2023 - National Acad Sciences
Every year, millions of brain MRI scans are acquired in hospitals, which is a figure
considerably larger than the size of any research dataset. Therefore, the ability to analyze …

Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review

P Moridian, N Ghassemi, M Jafari… - Frontiers in Molecular …, 2022 - frontiersin.org
Autism spectrum disorder (ASD) is a brain condition characterized by diverse signs and
symptoms that appear in early childhood. ASD is also associated with communication …

Assessment of human exposure to electromagnetic fields: Review and future directions

A Hirata, Y Diao, T Onishi, K Sasaki… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
This article reviews recent standardization activities and scientific studies related to the
assessment of human exposure to electromagnetic fields (EMF). The differences of human …

The ANTsX ecosystem for quantitative biological and medical imaging

NJ Tustison, PA Cook, AJ Holbrook, HJ Johnson… - Scientific reports, 2021 - nature.com
Abstract The Advanced Normalizations Tools ecosystem, known as ANTsX, consists of
multiple open-source software libraries which house top-performing algorithms used …

Convergence of artificial intelligence and neuroscience towards the diagnosis of neurological disorders—a scoping review

C Surianarayanan, JJ Lawrence, PR Chelliah… - Sensors, 2023 - mdpi.com
Artificial intelligence (AI) is a field of computer science that deals with the simulation of
human intelligence using machines so that such machines gain problem-solving and …

[HTML][HTML] Deep learning-based unlearning of dataset bias for MRI harmonisation and confound removal

NK Dinsdale, M Jenkinson, AIL Namburete - NeuroImage, 2021 - Elsevier
Increasingly large MRI neuroimaging datasets are becoming available, including many
highly multi-site multi-scanner datasets. Combining the data from the different scanners is …

AssemblyNet: A large ensemble of CNNs for 3D whole brain MRI segmentation

P Coupé, B Mansencal, M Clément, R Giraud… - NeuroImage, 2020 - Elsevier
Whole brain segmentation of fine-grained structures using deep learning (DL) is a very
challenging task since the number of anatomical labels is very high compared to the number …