Purpose To reduce radiotracer requirements for amyloid PET/MRI without sacrificing diagnostic quality by using deep learning methods. Materials and Methods Forty data sets from 39 patients (mean age ± standard deviation [SD], 67 years ± 8), including...
The relationship between neurocognition and functioning among patients with schizophrenia is well documented. However, integrating neuropsychological, clinical and psychopathological data to better investigate functional outcome still constitutes a c...
Computational intelligence and neuroscience
Dec 2, 2018
The accelerated growth of the percentage of elder people and persons with brain injury-related conditions and who are intellectually challenged are some of the main concerns of the developed countries. These persons often require special cares and ev...
Mild cognitive impairment (MCI) detection is important, such that appropriate interventions can be imposed to delay or prevent its progression to severe stages, including Alzheimer's disease (AD). Brain connectivity network inferred from the function...
Purpose To develop and validate a deep learning algorithm that predicts the final diagnosis of Alzheimer disease (AD), mild cognitive impairment, or neither at fluorine 18 (F) fluorodeoxyglucose (FDG) PET of the brain and compare its performance to t...
In this article, the authors aim to maximally utilize multimodality neuroimaging and genetic data for identifying Alzheimer's disease (AD) and its prodromal status, Mild Cognitive Impairment (MCI), from normal aging subjects. Multimodality neuroimagi...
OBJECTIVE: Alzheimer's disease (AD) is one of the most prevalent diseases among the adult population. The early detection of Mild Cognitive Impairment (MCI), which may trigger AD, is essential to slow down the cognitive decline process.
International journal of neural systems
Sep 20, 2018
The early detection of Alzheimer's disease and quantification of its progression poses multiple difficulties for machine learning algorithms. Two of the most relevant issues are related to missing data and results interpretability. To deal with both ...
PURPOSE: The confusion of MRI sequence names could be solved if MR images were automatically identified after image data acquisition. We revealed the ability of deep learning to classify head MRI sequences.
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
Sep 13, 2018
In Alzheimer's research, Mild Cognitive Impairment (MCI) is an important intermediate stage between normal aging and Alzheimer's. How to distinguish MCI samples that finally convert to AD from those do not is an essential problem in the prevention an...