KMS Chongqing Institute of Green and Intelligent Technology, CAS
Ranking convolutional neural network for Alzheimer's disease mini-mental state examination prediction at multiple time-points | |
Qiao, Hezhe1,2; Chen, Lin1; Zhu, Fan1 | |
2022 | |
摘要 | Background and objective: Alzheimer's disease (AD) is a fatal neurodegenerative disease. Predicting Mini mental state examination (MMSE) based on magnetic resonance imaging (MRI) plays an important role in monitoring the progress of AD. Existing machine learning based methods cast MMSE prediction as a single metric regression problem simply and ignore the relationship between subjects with various scores. Methods: In this study, we proposed a ranking convolutional neural network (rankCNN) to address the prediction of MMSE through muti-classification. Specifically, we use a 3D convolutional neural network with sharing weights to extract the feature from MRI, followed by multiple sub-networks which transform the cognitive regression into a series of simpler binary classification. In addition, we further use a ranking layer to measure the ranking information between samples to strengthen the ability of the classification by extracting more discriminative features. Results: We evaluated the proposed model on ADNI-1 and ADNI-2 datasets with a total of 1,569 subjects. The Root Mean Squared Error (RMSE) of our proposed model at baseline is 2 . 238 and 2 . 434 on ADNI-1 and ADNI-2, respectively. Extensive experimental results on ADNI-1 and ADNI-2 datasets demonstrate that our proposed model is superior to several state-of-theart methods at both baseline and future MMSE prediction of subjects. Conclusion: This paper provides a new method that can effectively predict the MMSE at baseline and future time points using baseline MRI, making it possible to use MRI for accurate early diagnosis of AD. The source code is freely available at https://github.com/fengduqianhe/ADrankCNN-master . (c) 2021 Elsevier B.V. All rights reserved. |
关键词 | Alzheimer's Disease (AD) Convolutional Neural Network (CNN) Magnetic Resonance Imaging (MRI) Mini-Mental State Examination (MMSE) Ranking learning |
DOI | 10.1016/j.cmpb.2021.106503 |
发表期刊 | COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE |
ISSN | 0169-2607 |
卷号 | 213页码:10 |
通讯作者 | Zhu, Fan(zhufan@cigit.ac.cn) |
收录类别 | SCI |
WOS记录号 | WOS:000720347300011 |
语种 | 英语 |