BACKGROUND: Metamemory training (MMT) is a useful training strategy for improving cognitive functioning in the older adult population. Despite the advantages, there are limitations imposed by location and time constraints.
The purpose of this study is to develop a deep learning method for thyroid delineation with high accuracy, efficiency, and robustness in noncontrast-enhanced head and neck CTs. The cross-sectional analysis consisted of six tests, including randomized...
The COVID-19 pandemic has created unprecedented challenges worldwide. Strained healthcare providers make difficult decisions on patient triage, treatment and care management on a daily basis. Policy makers have imposed social distancing measures to s...
Journal of neuroimaging : official journal of the American Society of Neuroimaging
Feb 15, 2021
BACKGROUND AND PURPOSE: Corpus callosum atrophy is a sensitive biomarker of multiple sclerosis (MS) neurodegeneration but typically requires manual 2D or volumetric 3D-based segmentations. We developed a supervised machine learning algorithm, DeepnCC...
Computer methods and programs in biomedicine
Feb 15, 2021
BACKGROUND: COVID-19 progresses slowly and negatively affects many people. However, mild to moderate symptoms develop in most infected people, who recover without hospitalization. Therefore, the development of early diagnosis and treatment strategies...
PURPOSE: To introduce a novel deep learning (DL) T2-weighted TSE imaging (T2) sequence in prostate MRI and investigate its impact on examination time, image quality, diagnostic confidence, and PI-RADS classification compared to standard T2-weighted T...
PURPOSE: Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disease. In recent years, machine learning methods have been widely used on analysis of neuroimage for quantitative evaluation and computer-aided diagnosis of AD or...
INTRODUCTION: Magnetic resonance imaging (MRI) has played an increasingly major role in the evaluation of patients with prostate cancer, although prostate MRI presents several technical challenges. Newer techniques, such as deep learning (DL), have b...
Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
Feb 12, 2021
PURPOSE: We assessed the ability of deep learning (DL) models to distinguish between tear meniscus of lacrimal duct obstruction (LDO) patients and normal subjects using anterior segment optical coherence tomography (ASOCT) images.
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