Diagnose Alzheimer's disease by combining 3D discrete wavelet transform and 3D moment invariants-Reference-Cited by-同舟云学术

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Diagnose Alzheimer's disease by combining 3D discrete wavelet transform and 3D moment invariants

Published:2022-08-08 Issue:14 Volume:16 Page:3948-3964
ISSN:1751-9659
Container-title:IET Image Processing
language:en
Short-container-title:IET Image Processing

Author:

Lao Huan¹²^ORCID,Zhang Xuejun³²⁴

Affiliation:

1. School of Artificial Intelligence Guangxi Minzu University Nanning Guangxi PR China

2. Medical College Guangxi University Nanning Guangxi PR China

3. School of Computer Electronics and Information Guangxi University Nanning Guangxi PR China

4. Guangxi Key Laboratory of Multimedia Communications and Network Technology Nanning Guangxi PR China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/ipr2.12605

Reference52 articles.

1. Nanomedicine and the Nervous System

2. 2018 Alzheimer's disease facts and figures

3. Emerging treatments for Alzheimer’s disease for non-amyloid and non-tau targets

4. Automatic classification of patients with Alzheimer's disease from structural MRI: A comparison of ten methods using the ADNI database

5. Multi-Method Analysis of MRI Images in Early Diagnostics of Alzheimer's Disease

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1. Diagnosis of Alzheimer's Disease Based on Structural Graph Convolutional Neural Networks;ACM Turing Award Celebration Conference 2024;2024-07-05

2. Stable and invertible invariants description for gray-level images based on Radon transform;The Visual Computer;2024-03-19

3. Machine learning with multimodal neuroimaging data to classify stages of Alzheimer’s disease: a systematic review and meta-analysis;Cognitive Neurodynamics;2023-08-18

4. Diagnosis of Alzheimer’s disease using hypergraph p-Laplacian regularized multi-task feature learning;Journal of Biomedical Informatics;2023-04

5. On The Potential of Image Moments for Medical Diagnosis;Journal of Imaging;2023-03-17

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