Alzheimer's disease
Although the prevalence of dementia continues to increase worldwide, incidence in the
western world might have decreased as a result of better vascular care and improved brain …
western world might have decreased as a result of better vascular care and improved brain …
Brain atrophy in Alzheimer's disease and aging
Thanks to its safety and accessibility, magnetic resonance imaging (MRI) is extensively used
in clinical routine and research field, largely contributing to our understanding of the …
in clinical routine and research field, largely contributing to our understanding of the …
[HTML][HTML] A multi-model deep convolutional neural network for automatic hippocampus segmentation and classification in Alzheimer's disease
Alzheimer's disease (AD) is a progressive and irreversible brain degenerative disorder. Mild
cognitive impairment (MCI) is a clinical precursor of AD. Although some treatments can …
cognitive impairment (MCI) is a clinical precursor of AD. Although some treatments can …
Sam on medical images: A comprehensive study on three prompt modes
The Segment Anything Model (SAM) made an eye-catching debut recently and inspired
many researchers to explore its potential and limitation in terms of zero-shot generalization …
many researchers to explore its potential and limitation in terms of zero-shot generalization …
QuickNAT: A fully convolutional network for quick and accurate segmentation of neuroanatomy
Whole brain segmentation from structural magnetic resonance imaging (MRI) is a
prerequisite for most morphological analyses, but is computationally intense and can …
prerequisite for most morphological analyses, but is computationally intense and can …
Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials
MW Weiner, DP Veitch, PS Aisen, LA Beckett… - Alzheimer's & …, 2017 - Elsevier
Abstract Introduction The Alzheimer's Disease Neuroimaging Initiative (ADNI) has continued
development and standardization of methodologies for biomarkers and has provided an …
development and standardization of methodologies for biomarkers and has provided an …
A deep learning model for early prediction of Alzheimer's disease dementia based on hippocampal magnetic resonance imaging data
Introduction It is challenging at baseline to predict when and which individuals who meet
criteria for mild cognitive impairment (MCI) will ultimately progress to Alzheimer's disease …
criteria for mild cognitive impairment (MCI) will ultimately progress to Alzheimer's disease …
Non-rigid image registration using self-supervised fully convolutional networks without training data
A novel non-rigid image registration algorithm is built upon fully convolutional networks
(FCNs) to optimize and learn spatial transformations between pairs of images to be …
(FCNs) to optimize and learn spatial transformations between pairs of images to be …
Clinical and cognitive trajectories in cognitively healthy elderly individuals with suspected non-Alzheimer's disease pathophysiology (SNAP) or Alzheimer's disease …
Background Brain amyloid β (Aβ) deposition and neurodegeneration have been
documented in about 50–60% of cognitively healthy elderly individuals (aged 60 years or …
documented in about 50–60% of cognitively healthy elderly individuals (aged 60 years or …
Medical image understanding with pretrained vision language models: A comprehensive study
The large-scale pre-trained vision language models (VLM) have shown remarkable domain
transfer capability on natural images. However, it remains unknown whether this capability …
transfer capability on natural images. However, it remains unknown whether this capability …