AIMC Topic: Frontotemporal Dementia
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Artificial Intelligence Based Hierarchical Classification of Frontotemporal Dementia.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Frontotemporal dementia (FTD) is a typical kind of presenile dementia with three main subtypes: behavioral-variant FTD (bvFTD), non-fluent variant primary progressive aphasia (nfvPPA), and semantic variant primary progressive aphasia (svPPA). Our aim...
Quantitative Assessment of Fundus Tessellated Density in Highly Myopic Glaucoma Using Deep Learning.
Translational vision science & technology
Apr 2, 2024
PURPOSE: To characterize the fundus tessellated density (FTD) in highly myopic glaucoma (HMG) and high myopia (HM) for discovering early signs and diagnostic markers.
[Preliminary study on automatic quantification and grading of leopard spots fundus based on deep learning technology].
[Zhonghua yan ke za zhi] Chinese journal of ophthalmology
Mar 11, 2024
To achieve automatic segmentation, quantification, and grading of different regions of leopard spots fundus (FT) using deep learning technology. The analysis includes exploring the correlation between novel quantitative indicators, leopard spot fund...
A Deep-Learning Enabled Automatic Fetal Thalamus Diameter Measurement Algorithm.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2023
The analysis of maternal factors that impact the normal development of the fetal thalamus is an emerging field of research and requires the retrospective measurement of fetal thalamus diameter (FTD). Unfortunately, FTD is not measured in routine 2D u...
Fundus Tessellated Density Assessed by Deep Learning in Primary School Children.
Translational vision science & technology
Jun 1, 2023
PURPOSE: To explore associations of fundus tessellated density (FTD) and compare characteristics of different fundus tessellation (FT) distribution patterns, based on artificial intelligence technology using deep learning.
In Vivo Assay of Cortical Microcircuitry in Frontotemporal Dementia: A Platform for Experimental Medicine Studies.
Cerebral cortex (New York, N.Y. : 1991)
Feb 5, 2021
The analysis of neural circuits can provide crucial insights into the mechanisms of neurodegeneration and dementias, and offer potential quantitative biological tools to assess novel therapeutics. Here we use behavioral variant frontotemporal dementi...
Applying Automated MR-Based Diagnostic Methods to the Memory Clinic: A Prospective Study.
Journal of Alzheimer's disease : JAD
Jan 1, 2015
Several studies have demonstrated that fully automated pattern recognition methods applied to structural magnetic resonance imaging (MRI) aid in the diagnosis of dementia, but these conclusions are based on highly preselected samples that significant...
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