[HTML][HTML] Image harmonization: A review of statistical and deep learning methods for removing batch effects and evaluation metrics for effective harmonization
Magnetic resonance imaging and computed tomography from multiple batches (eg sites,
scanners, datasets, etc.) are increasingly used alongside complex downstream analyses to …
scanners, datasets, etc.) are increasingly used alongside complex downstream analyses to …
Functional connectomics in depression: insights into therapies
Depression is a common mental disorder characterized by heterogeneous cognitive and
behavioral symptoms. The emerging research paradigm of functional connectomics has …
behavioral symptoms. The emerging research paradigm of functional connectomics has …
Braingb: a benchmark for brain network analysis with graph neural networks
Mapping the connectome of the human brain using structural or functional connectivity has
become one of the most pervasive paradigms for neuroimaging analysis. Recently, Graph …
become one of the most pervasive paradigms for neuroimaging analysis. Recently, Graph …
Mitigating site effects in covariance for machine learning in neuroimaging data
To acquire larger samples for answering complex questions in neuroscience, researchers
have increasingly turned to multi‐site neuroimaging studies. However, these studies are …
have increasingly turned to multi‐site neuroimaging studies. However, these studies are …
A multi-site, multi-disorder resting-state magnetic resonance image database
Abstract Machine learning classifiers for psychiatric disorders using resting-state functional
magnetic resonance imaging (rs-fMRI) have recently attracted attention as a method for …
magnetic resonance imaging (rs-fMRI) have recently attracted attention as a method for …
Precision functional MRI mapping reveals distinct connectivity patterns for depression associated with traumatic brain injury
SH Siddiqi, S Kandala, CD Hacker… - Science translational …, 2023 - science.org
Depression associated with traumatic brain injury (TBI) is believed to be clinically distinct
from primary major depressive disorder (MDD) and may be less responsive to conventional …
from primary major depressive disorder (MDD) and may be less responsive to conventional …
Variability and standardization of quantitative imaging: monoparametric to multiparametric quantification, radiomics, and artificial intelligence
Radiological images have been assessed qualitatively in most clinical settings by the expert
eyes of radiologists and other clinicians. On the other hand, quantification of radiological …
eyes of radiologists and other clinicians. On the other hand, quantification of radiological …
Closing the life-cycle of normative modeling using federated hierarchical Bayesian regression
Clinical neuroimaging data availability has grown substantially in the last decade, providing
the potential for studying heterogeneity in clinical cohorts on a previously unprecedented …
the potential for studying heterogeneity in clinical cohorts on a previously unprecedented …
Challenges of implementing computer-aided diagnostic models for neuroimages in a clinical setting
Advances in artificial intelligence have cultivated a strong interest in developing and
validating the clinical utilities of computer-aided diagnostic models. Machine learning for …
validating the clinical utilities of computer-aided diagnostic models. Machine learning for …
Comparison of traveling‐subject and ComBat harmonization methods for assessing structural brain characteristics
N Maikusa, Y Zhu, A Uematsu… - Human brain …, 2021 - Wiley Online Library
Multisite magnetic resonance imaging (MRI) is increasingly used in clinical research and
development. Measurement biases—caused by site differences in scanner/image …
development. Measurement biases—caused by site differences in scanner/image …