基于计算机辅助诊断技术的阿尔兹海默症早期分类研究综述
楚阳， 徐文龙 - 计算机工程与科学, 2022 - joces.nudt.edu.cn
阿尔兹海默症(AD) 作为主要的神经退行性疾病之一, 已成为导致痴呆问题最常见的原因.
截至目前, 尚缺乏有效的针对性治疗药物和阻止疾病发展的有效治疗方式 …
截至目前, 尚缺乏有效的针对性治疗药物和阻止疾病发展的有效治疗方式 …
Benchmarking geometric deep learning for cortical segmentation and neurodevelopmental phenotype prediction
The emerging field of geometric deep learning extends the application of convolutional
neural networks to irregular domains such as graphs, meshes and surfaces. Several recent …
neural networks to irregular domains such as graphs, meshes and surfaces. Several recent …
Predictive modelling of brain disorders with magnetic resonance imaging: A systematic review of modelling practices, transparency, and interpretability in the use of …
Brain disorders comprise several psychiatric and neurological disorders which can be
characterized by impaired cognition, mood alteration, psychosis, depressive episodes, and …
characterized by impaired cognition, mood alteration, psychosis, depressive episodes, and …
Neurodevelopmental Phenotype Prediction: A State-of-the-Art Deep Learning Model
D Unyi, B Gyires-Tóth - Machine Learning for Health, 2022 - proceedings.mlr.press
A major challenge in medical image analysis is the automated detection of biomarkers from
neuroimaging data. Traditional approaches, often based on image registration, are limited in …
neuroimaging data. Traditional approaches, often based on image registration, are limited in …
Multimodal Identification of Alzheimer's Disease: A Review
G Fang, M Liu, Y Zhong, Z Zhang, J Huang… - arXiv preprint arXiv …, 2023 - arxiv.org
Alzheimer's disease is a progressive neurological disorder characterized by cognitive
impairment and memory loss. With the increasing aging population, the incidence of AD is …
impairment and memory loss. With the increasing aging population, the incidence of AD is …
Alzheimer's disease classification using capsule networks on structural MRI
AF Nagashbayev, M Fatih Demirci - Proceedings of the 2020 5th …, 2020 - dl.acm.org
Alzheimer's disease (AD) is the most prevalent cause of dementia among elderly people.
This paper presents a deep learning model based on capsule networks for the classification …
This paper presents a deep learning model based on capsule networks for the classification …
SurfGNN: A robust surface-based prediction model with interpretability for coactivation maps of spatial and cortical features
Z Li, J Zhang, Y Zeng, J Lin, D Zhang, J Zhang… - arXiv preprint arXiv …, 2024 - arxiv.org
Current brain surface-based prediction models often overlook the variability of regional
attributes at the cortical feature level. While graph neural networks (GNNs) excel at capturing …
attributes at the cortical feature level. While graph neural networks (GNNs) excel at capturing …
Unsupervised Learning of Cortical Surface Registration Using Spherical Harmonics
We present novel learning-based spherical registration using the spherical harmonics. Our
goal is to achieve a continuous and smooth warp field that can effectively facilitate precise …
goal is to achieve a continuous and smooth warp field that can effectively facilitate precise …
Review of early classification of Alzheimer s disease based on computer-aided diagnosis technology
Y CHU, W XU - Computer Engineering & Science, 2022 - joces.nudt.edu.cn
As one of the major neurodegenerative diseases, Alzheimer s disease (AD) has become
the most common cause of dementia. Up to now, there is still a lack of effective targeted …
the most common cause of dementia. Up to now, there is still a lack of effective targeted …
Structure-aware neural networks in the study of multi-modal population cohorts: an application to mental health
C Ambroise - 2024 - theses.hal.science
It is currently acknowledged that relying solely on conventional classification strategies from
a single data source is not effective to understand, diagnose or prognose psychiatric …
a single data source is not effective to understand, diagnose or prognose psychiatric …