Computer-aided diagnosis of Alzheimer’s disease through weak supervision deep learning Framework with attention mechanism

  • Alzheimer’s disease (AD) is the most prevalent neurodegenerative disease causing dementia and poses significant health risks to middle-aged and elderly people. Brain magnetic resonance imaging (MRI) is the most widely used diagnostic method for AD. However, it is challenging to collect sufficient brain imaging data with high-quality annotations. Weakly supervised learning (WSL) is a machine learning technique aimed at learning effective feature representation from limited or low-quality annotations. In this paper, we propose a WSL-based deep learning (DL) framework (ADGNET) consisting of a backbone network with an attention mechanism and a task network for simultaneous image classification and image reconstruction to identify and classify AD using limited annotations. The ADGNET achieves excellent performance based on six evaluation metrics (Kappa, sensitivity, specificity, precision, accuracy, F1-score) on two brain MRI datasets (2D MRI and 3D MRI data) using fine-tuning with only 20% of the labels from both datasets. The ADGNET has an F1-score of 99.61% and sensitivity is 99.69%, outperforming two state-of-the-art models (ResNext WSL and SimCLR). The proposed method represents a potential WSL-based computer-aided diagnosis method for AD in clinical practice.

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Author:Shuang LiangORCiD, Yu GuORCiD
Parent Title (English):Sensors
Place of publication:Basel
Document Type:Article
Date of Publication (online):2020/12/31
Date of first Publication:2020/12/31
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2023/08/30
Tag:Alzheimer’s disease; CNN; attention module; computer-aided diagnosis; magnetic resonance imaging; multi-task learning; weakly supervised learning
Issue:1, art. 220
Article Number:220
Page Number:15
First Page:1
Last Page:15
This research was funded by the Ministry of Science and Technology of the People’s Republic of China (Grant No. 2017YFB1400100) and the National Natural Science Foundation of China (Grant No. 61876059).
Institutes:Biochemie, Chemie und Pharmazie
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 54 Chemie / 540 Chemie und zugeordnete Wissenschaften
6 Technik, Medizin, angewandte Wissenschaften / 60 Technik / 600 Technik, Technologie
6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International