Psychiatric illnesses are heterogeneous in nature. No illness manifests in the same way across individuals, and no two patients with a shared diagnosis exhibit identical symptom profiles. Over the last several decades, group-level analyses of in vivo...
AJNR. American journal of neuroradiology
Sep 29, 2022
BACKGROUND AND PURPOSE: Synthetic MR imaging is a time-efficient technique. However, its rather long scan time can be challenging for children. This study aimed to evaluate the clinical feasibility of accelerated synthetic MR imaging with deep learni...
Although deep learning holds great promise as a prognostic tool in psychiatry, a limitation of the method is that it requires large training sample sizes to achieve replicable accuracy. This is problematic for fMRI datasets as they are typically smal...
INTRODUCTION: Deep learning-based MRI reconstruction has recently been introduced to improve image quality. This study aimed to evaluate the performance of deep learning reconstruction in pediatric brain MRI.
Epilepsy is a disorder of the brain denoted by frequent seizures. The symptoms of seizure include confusion, abnormal staring, and rapid, sudden, and uncontrollable hand movements. Epileptic seizure detection methods involve neurological exams, blood...
Functional magnetic resonance imaging (fMRI) has been shown successfully to assess and stratify patients with painful diabetic peripheral neuropathy (pDPN). This supports the idea of using neuroimaging as a mechanism-based technique to individualise ...
Machine learning (ML) has been extensively applied in brain imaging studies to aid the diagnosis of psychiatric disorders and the selection of potential biomarkers. Due to the high dimensionality of imaging data and heterogeneous subtypes of psychiat...
Understanding the brain's functional architecture has been an important topic in the neuroimaging field. A variety of brain network modeling methods have been proposed. Recently, deep neural network-based methods have shown a great advantage in model...
Force and effort are important components of a motor task that can impact rehabilitation effectiveness. However, few studies have evaluated the impact of these factors on cortical activation during gait. The purpose of the study was to investigate th...
Brain-age (BA) estimates based on deep learning are increasingly used as neuroimaging biomarker for brain health; however, the underlying neural features have remained unclear. We combined ensembles of convolutional neural networks with Layer-wise Re...