BACKGROUND: Convolutional neural network (CNN) can capture the structural features changes of brain aging based on MRI, thus predict brain age in healthy individuals accurately. However, most studies use single feature to predict brain age in healthy...
Journal of imaging informatics in medicine
Jul 19, 2024
Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder characterized by a reduced attention span, hyperactivity, and impulsive behaviors, which typically manifest during childhood. This study employs functional magnetic reso...
Differential diagnosis of acute loss of consciousness (LOC) is crucial due to the need for different therapeutic strategies despite similar clinical presentations among etiologies such as nonconvulsive status epilepticus, metabolic encephalopathy, an...
The brain may have evolved a modular architecture for daily tasks, with circuits featuring functionally specialized modules that match the task structure. We hypothesize that this architecture enables better learning and generalization than architect...
IEEE transactions on bio-medical engineering
Jul 18, 2024
Resting-state functional magnetic resonance imaging (rs-fMRI) can reflect spontaneous neural activities in the brain and is widely used for brain disorder analysis. Previous studies focus on extracting fMRI representations using machine/deep learning...
International journal of neural systems
Jul 17, 2024
Recently, Graph Neural Networks (GNNs) have gained widespread application in automatic brain network classification tasks, owing to their ability to directly capture crucial information in non-Euclidean structures. However, two primary challenges per...
Cancer, a multifaceted and pernicious disease, continuously challenges medicine, requiring innovative treatments. Brain cancers pose unique and daunting challenges due to the intricacies of the central nervous system and the blood-brain barrier. In t...
IEEE journal of translational engineering in health and medicine
Jul 17, 2024
Brain microstructural changes already occur in the earliest phases of Alzheimer's disease (AD) as evidenced in diffusion magnetic resonance imaging (dMRI) literature. This study investigates the potential of the novel dMRI Apparent Measures Using Red...
This research paper introduces an efficient approach for the segmentation of active and inactive plaques within Fluid-attenuated inversion recovery (FLAIR) images, employing a convolutional neural network (CNN) model known as DeepLabV3Plus SE with th...
Recent unsupervised domain adaptation (UDA) methods in medical image segmentation commonly utilize Generative Adversarial Networks (GANs) for domain translation. However, the translated images often exhibit a distribution deviation from the ideal due...
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