Domain adaptation for medical image analysis: a survey
Machine learning techniques used in computer-aided medical image analysis usually suffer
from the domain shift problem caused by different distributions between source/reference …
from the domain shift problem caused by different distributions between source/reference …
Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review
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 …
symptoms that appear in early childhood. ASD is also associated with communication …
rs-fMRI and machine learning for ASD diagnosis: a systematic review and meta-analysis
Abstract Autism Spectrum Disorder (ASD) diagnosis is still based on behavioral criteria
through a lengthy and time-consuming process. Much effort is being made to identify brain …
through a lengthy and time-consuming process. Much effort is being made to identify brain …
A survey on deep learning for neuroimaging-based brain disorder analysis
Deep learning has recently been used for the analysis of neuroimages, such as structural
magnetic resonance imaging (MRI), functional MRI, and positron emission tomography …
magnetic resonance imaging (MRI), functional MRI, and positron emission tomography …
Transfer learning in magnetic resonance brain imaging: A systematic review
(1) Background: Transfer learning refers to machine learning techniques that focus on
acquiring knowledge from related tasks to improve generalization in the tasks of interest. In …
acquiring knowledge from related tasks to improve generalization in the tasks of interest. In …
Multicenter and multichannel pooling GCN for early AD diagnosis based on dual-modality fused brain network
For significant memory concern (SMC) and mild cognitive impairment (MCI), their
classification performance is limited by confounding features, diverse imaging protocols, and …
classification performance is limited by confounding features, diverse imaging protocols, and …
Unsupervised cross-domain functional MRI adaptation for automated major depressive disorder identification
Resting-state functional magnetic resonance imaging (rs-fMRI) data have been widely used
for automated diagnosis of brain disorders such as major depressive disorder (MDD) to …
for automated diagnosis of brain disorders such as major depressive disorder (MDD) to …
Disease-image-specific learning for diagnosis-oriented neuroimage synthesis with incomplete multi-modality data
Incomplete data problem is commonly existing in classification tasks with multi-source data,
particularly the disease diagnosis with multi-modality neuroimages, to track which, some …
particularly the disease diagnosis with multi-modality neuroimages, to track which, some …
Interactive computer-aided diagnosis on medical image using large language models
Computer-aided diagnosis (CAD) has advanced medical image analysis, while large
language models (LLMs) have shown potential in clinical applications. However, LLMs …
language models (LLMs) have shown potential in clinical applications. However, LLMs …
Multi-site clustering and nested feature extraction for identifying autism spectrum disorder with resting-state fMRI
Brain functional connectivity (FC) derived from resting-state functional magnetic resonance
imaging (rs-fMRI) has been widely employed to study neuropsychiatric disorders such as …
imaging (rs-fMRI) has been widely employed to study neuropsychiatric disorders such as …