[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 …
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 …
[HTML][HTML] Applications of generative adversarial networks in neuroimaging and clinical neuroscience
Generative adversarial networks (GANs) are one powerful type of deep learning models that
have been successfully utilized in numerous fields. They belong to the broader family of …
have been successfully utilized in numerous fields. They belong to the broader family of …
Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium
D Schijven, MC Postema… - Proceedings of the …, 2023 - National Acad Sciences
Left–right asymmetry is an important organizing feature of the healthy brain that may be
altered in schizophrenia, but most studies have used relatively small samples and …
altered in schizophrenia, but most studies have used relatively small samples and …
In vivo white matter microstructure in adolescents with early-onset psychosis: a multi-site mega-analysis
Emerging evidence suggests brain white matter alterations in adolescents with early-onset
psychosis (EOP; age of onset< 18 years). However, as neuroimaging methods vary and …
psychosis (EOP; age of onset< 18 years). However, as neuroimaging methods vary and …
Prediction of the information processing speed performance in multiple sclerosis using a machine learning approach in a large multicenter magnetic resonance …
Many patients with multiple sclerosis (MS) experience information processing speed (IPS)
deficits, and the Symbol Digit Modalities Test (SDMT) has been recommended as a valid …
deficits, and the Symbol Digit Modalities Test (SDMT) has been recommended as a valid …
Effects of MRI scanner manufacturers in classification tasks with deep learning models
Deep learning has become a leading subset of machine learning and has been successfully
employed in diverse areas, ranging from natural language processing to medical image …
employed in diverse areas, ranging from natural language processing to medical image …
Improving Alzheimer's disease diagnosis with multi-modal PET embedding features by a 3D multi-task MLP-mixer neural network
Positron emission tomography (PET) with fluorodeoxyglucose (FDG) or florbetapir (AV45)
has been proved effective in the diagnosis of Alzheimer's disease. However, the expensive …
has been proved effective in the diagnosis of Alzheimer's disease. However, the expensive …
Cortical morphology in patients with the deficit and non-deficit syndrome of schizophrenia: a worldwide meta-and mega-analyses
N Banaj, D Vecchio, F Piras, P De Rossi, J Bustillo… - Molecular …, 2023 - nature.com
Converging evidence suggests that schizophrenia (SZ) with primary, enduring negative
symptoms (ie, Deficit SZ (DSZ)) represents a distinct entity within the SZ spectrum while the …
symptoms (ie, Deficit SZ (DSZ)) represents a distinct entity within the SZ spectrum while the …
[HTML][HTML] A systematic comparison of VBM pipelines and their application to age prediction
Voxel-based morphometry (VBM) analysis is commonly used for localized quantification of
gray matter volume (GMV). Several alternatives exist to implement a VBM pipeline …
gray matter volume (GMV). Several alternatives exist to implement a VBM pipeline …