AIMC Topic: Aged, 80 and over
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Learning-based single-step quantitative susceptibility mapping reconstruction without brain extraction.
NeuroImage
Aug 1, 2019
Quantitative susceptibility mapping (QSM) estimates the underlying tissue magnetic susceptibility from MRI gradient-echo phase signal and typically requires several processing steps. These steps involve phase unwrapping, brain volume extraction, back...
Clinical effects of robot-assisted gait training and treadmill training for Parkinson's disease. A randomized controlled trial.
Annals of physical and rehabilitation medicine
Aug 1, 2019
BACKGROUND: Although gait disorders strongly contribute to perceived disability in people with Parkinson's disease, clinical trials have failed to identify which task-oriented gait training method can provide the best benefit. Freezing of gait remain...
Characterizing Alzheimer's Disease With Image and Genetic Biomarkers Using Supervised Topic Models.
IEEE journal of biomedical and health informatics
Jul 31, 2019
Neuroimaging and genetic biomarkers have been widely studied from discriminative perspectives towards Alzheimer's disease (AD) classification, since neuroanatomical patterns and genetic variants are jointly critical indicators for AD diagnosis. Gener...
Telepresence robots: Encouraging interactive communication between family carers and people with dementia.
Australasian journal on ageing
Jul 31, 2019
OBJECTIVE: The aim of the study was to explore the feasibility of using telepresence robots to encourage interactive communication in dementia care, from the perspective of family carers.
Automated lesion segmentation with BIANCA: Impact of population-level features, classification algorithm and locally adaptive thresholding.
NeuroImage
Jul 31, 2019
White matter hyperintensities (WMH) or white matter lesions exhibit high variability in their characteristics both at population- and subject-level, making their detection a challenging task. Population-level factors such as age, vascular risk factor...
Artificial neural networks reveal individual differences in metacognitive monitoring of memory.
PloS one
Jul 31, 2019
Previous work supports an age-specific impairment for recognition memory of pairs of words and other stimuli. The present study tested the generalization of an associative deficit across word, name, and nonword stimulus types in younger and older adu...
Performance of deep learning for differentiating pancreatic diseases on contrast-enhanced magnetic resonance imaging: A preliminary study.
Diagnostic and interventional imaging
Jul 30, 2019
PURPOSE: The purpose of this study was to evaluate the ability of deep learning to differentiate pancreatic diseases on contrast-enhanced magnetic resonance (MR) images with the aid of generative adversarial network (GAN).
A whole slide image-based machine learning approach to predict ductal carcinoma in situ (DCIS) recurrence risk.
Breast cancer research : BCR
Jul 29, 2019
BACKGROUND: Breast ductal carcinoma in situ (DCIS) represent approximately 20% of screen-detected breast cancers. The overall risk for DCIS patients treated with breast-conserving surgery stems almost exclusively from local recurrence. Although a mas...
Deep learning approaches using 2D and 3D convolutional neural networks for generating male pelvic synthetic computed tomography from magnetic resonance imaging.
Medical physics
Jul 26, 2019
PURPOSE: The improved soft tissue contrast of magnetic resonance imaging (MRI) compared to computed tomography (CT) makes it a useful imaging modality for radiotherapy treatment planning. Even when MR images are acquired for treatment planning, the s...
Convolutional Neural Network for Automated FLAIR Lesion Segmentation on Clinical Brain MR Imaging.
AJNR. American journal of neuroradiology
Jul 25, 2019
BACKGROUND AND PURPOSE: Most brain lesions are characterized by hyperintense signal on FLAIR. We sought to develop an automated deep learning-based method for segmentation of abnormalities on FLAIR and volumetric quantification on clinical brain MRIs...
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