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[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 …
[HTML][HTML] Harmonization strategies in multicenter MRI-based radiomics
Radiomics analysis is a powerful tool aiming to provide diagnostic and prognostic patient
information directly from images that are decoded into handcrafted features, comprising …
information directly from images that are decoded into handcrafted features, comprising …
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 …
Increasing diversity in connectomics with the Chinese Human Connectome Project
Cultural differences and biological diversity play important roles in sha** human brain
structure and function. To date, most large-scale multimodal neuroimaging datasets have …
structure and function. To date, most large-scale multimodal neuroimaging datasets have …
HACA3: A unified approach for multi-site MR image harmonization
The lack of standardization and consistency of acquisition is a prominent issue in magnetic
resonance (MR) imaging. This often causes undesired contrast variations in the acquired …
resonance (MR) imaging. This often causes undesired contrast variations in the acquired …
Addressing multi‐site functional MRI heterogeneity through dual‐expert collaborative learning for brain disease identification
Several studies employ multi‐site rs‐fMRI data for major depressive disorder (MDD)
identification, with a specific site as the to‐be‐analyzed target domain and other site (s) as …
identification, with a specific site as the to‐be‐analyzed target domain and other site (s) as …
The status of MRI databases across the world focused on psychiatric and neurological disorders
Neuroimaging databases for neuro‐psychiatric disorders enable researchers to implement
data‐driven research approaches by providing access to rich data that can be used to study …
data‐driven research approaches by providing access to rich data that can be used to study …
Deepcombat: A statistically motivated, hyperparameter‐robust, deep learning approach to harmonization of neuroimaging data
Neuroimaging data acquired using multiple scanners or protocols are increasingly
available. However, such data exhibit technical artifacts across batches which introduce …
available. However, such data exhibit technical artifacts across batches which introduce …
[HTML][HTML] IGUANe: A 3D generalizable CycleGAN for multicenter harmonization of brain MR images
In MRI studies, the aggregation of imaging data from multiple acquisition sites enhances
sample size but may introduce site-related variabilities that hinder consistency in …
sample size but may introduce site-related variabilities that hinder consistency in …
Segmentation-guided domain adaptation and data harmonization of multi-device retinal optical coherence tomography using cycle-consistent generative adversarial …
Background Medical images such as Optical Coherence Tomography (OCT) images
acquired from different devices may show significantly different intensity profiles. An …
acquired from different devices may show significantly different intensity profiles. An …