The use of neuroimaging techniques in the early and differential diagnosis of dementia
L Chouliaras, JT O'Brien - Molecular Psychiatry, 2023 - nature.com
Dementia is a leading cause of disability and death worldwide. At present there is no
disease modifying treatment for any of the most common types of dementia such as …
disease modifying treatment for any of the most common types of dementia such as …
The role of generative adversarial networks in brain MRI: a scoping review
The performance of artificial intelligence (AI) for brain MRI can improve if enough data are
made available. Generative adversarial networks (GANs) showed a lot of potential to …
made available. Generative adversarial networks (GANs) showed a lot of potential to …
Multimodal deep learning for Alzheimer's disease dementia assessment
Worldwide, there are nearly 10 million new cases of dementia annually, of which
Alzheimer's disease (AD) is the most common. New measures are needed to improve the …
Alzheimer's disease (AD) is the most common. New measures are needed to improve the …
Deep learning-based diagnosis of Alzheimer's disease
Alzheimer's disease (AD), the most familiar type of dementia, is a severe concern in modern
healthcare. Around 5.5 million people aged 65 and above have AD, and it is the sixth …
healthcare. Around 5.5 million people aged 65 and above have AD, and it is the sixth …
Phenotypic categorisation of individual subjects with motor neuron disease based on radiological disease burden patterns: a machine-learning approach
Motor neuron disease is an umbrella term encompassing a multitude of clinically
heterogeneous phenotypes. The early and accurate categorisation of patients is hugely …
heterogeneous phenotypes. The early and accurate categorisation of patients is hugely …
The use of generative adversarial networks in medical image augmentation
A Makhlouf, M Maayah, N Abughanam… - Neural Computing and …, 2023 - Springer
Abstract Generative Adversarial Networks (GANs) have been widely applied in various
domains, including medical image analysis. GANs have been utilized in classification and …
domains, including medical image analysis. GANs have been utilized in classification and …
Alzheimer's Disease Detection Using Deep Learning on Neuroimaging: A Systematic Review
Alzheimer's disease (AD) is a pressing global issue, demanding effective diagnostic
approaches. This systematic review surveys the recent literature (2018 onwards) to …
approaches. This systematic review surveys the recent literature (2018 onwards) to …
Lf-unet–a novel anatomical-aware dual-branch cascaded deep neural network for segmentation of retinal layers and fluid from optical coherence tomography images
Computer-assistant diagnosis of retinal disease relies heavily on the accurate detection of
retinal boundaries and other pathological features such as fluid accumulation. Optical …
retinal boundaries and other pathological features such as fluid accumulation. Optical …
Clinical explainable differential diagnosis of polypoidal choroidal vasculopathy and age-related macular degeneration using deep learning
Background This study aims to achieve an automatic differential diagnosis between two
types of retinal pathologies with similar pathological features-Polypoidal choroidal …
types of retinal pathologies with similar pathological features-Polypoidal choroidal …
Deep learning-based approach for multi-stage diagnosis of Alzheimer's disease
Alzheimer's Disease (AD) is a common neurological brain disorder that causes the brain
cells to die and shrink (Atrophy) gradually, resulting in a continuous decline in one's ability to …
cells to die and shrink (Atrophy) gradually, resulting in a continuous decline in one's ability to …