Quantitative susceptibility mapping (QSM) provides a valuable MRI contrast mechanism that has demonstrated broad clinical applications. However, the image reconstruction of QSM is challenging due to its ill-posed dipole inversion process. In this stu...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Dec 25, 2020
Convolutional neural networks (CNNs) have become an increasingly popular tool for brain lesion segmentation in recent years due to its accuracy and efficiency. However, CNN-based brain lesion segmentation generally requires a large amount of annotate...
Neural networks : the official journal of the International Neural Network Society
Dec 23, 2020
In recent years, deep learning has emerged as a powerful tool for developing Brain-Computer Interface (BCI) systems. However, for deep learning models trained entirely on the data from a specific individual, the performance increase has only been mar...
Neural networks : the official journal of the International Neural Network Society
Dec 23, 2020
Recently, the focus of functional connectivity analysis of human brain has shifted from merely revealing the inter-regional functional correlation over the entire scan duration to capturing the time-varying information of brain networks and character...
OBJECTIVE: We assessed preoperative structural brain networks and clinical characteristics of patients with drug-resistant temporal lobe epilepsy (TLE) to identify correlates of postsurgical seizure recurrences.
Alzheimer's disease (AD) is a neurodegenerative disease with an irreversible and progressive process. To understand the brain functions and identify the biomarkers of AD and early stages of the disease [also known as, mild cognitive impairment (MCI)]...
Mindfulness training is associated with improvements in psychological wellbeing and cognition, yet the specific underlying neurophysiological mechanisms underpinning these changes are uncertain. This study uses a novel brain-inspired artificial neura...
Journal of applied clinical medical physics
Dec 19, 2020
PURPOSE: The purpose of this study was to develop automated planning for whole-brain radiation therapy (WBRT) using a U-net-based deep-learning model for predicting the multileaf collimator (MLC) shape bypassing the contouring processes.
PURPOSE: In order to improve the reconstruction accuracy of magnetic induction tomography (MIT) and achieve fast imaging especially in the detection of cerebral hemorrhage, artificial intelligence algorithms are proposed to improve the accuracy of MI...
Measurement of stimulus-induced dopamine release and other types of transient neurotransmitter response (TNR) from dynamic positron emission tomography (PET) images typically suffers from limited detection sensitivity and high false positive (FP) rat...
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