Abstract
Aim. Alzheimer’s disease (AD) is a chronic neurodegenerative disease. Recently, computer scientists have developed various methods for early detection based on computer vision and machine learning techniques.Method. In this study, we proposed a novel AD detection method by displacement field (DF) estimation between a normal brain and an AD brain. The DF was treated as the AD-related features, reduced by principal component analysis (PCA), and finally fed into three classifiers: support vector machine (SVM), generalized eigenvalue proximal SVM (GEPSVM), and twin SVM (TSVM). The 10-fold cross validation repeated 50 times.Results. The results showed the “DF + PCA + TSVM” achieved the accuracy of 92.75 ± 1.77, sensitivity of 90.56 ± 1.15, specificity of 93.37 ± 2.05, and precision of 79.61 ± 2.21. This result is better than or comparable with not only the other proposed two methods, but also ten state-of-the-art methods. Besides, our method discovers the AD is related to following brain regions disclosed in recent publications: Angular Gyrus, Anterior Cingulate, Cingulate Gyrus, Culmen, Cuneus, Fusiform Gyrus, Inferior Frontal Gyrus, Inferior Occipital Gyrus, Inferior Parietal Lobule, Inferior Semi-Lunar Lobule, Inferior Temporal Gyrus, Insula, Lateral Ventricle, Lingual Gyrus, Medial Frontal Gyrus, Middle Frontal Gyrus, Middle Occipital Gyrus, Middle Temporal Gyrus, Paracentral Lobule, Parahippocampal Gyrus, Postcentral Gyrus, Posterior Cingulate, Precentral Gyrus, Precuneus, Sub-Gyral, Superior Parietal Lobule, Superior Temporal Gyrus, Supramarginal Gyrus, and Uncus.Conclusion. The displacement filed is effective in detection of AD and related brain-regions.
Highlights
Alzheimer’s disease (AD) is an abnormal process of aging
AD is a special category of senile dementia (SD) which leads to short-term and long-term memory, thinking, and behavior (Dong et al, 2015a)
Method of region detection Here, we proposed a visual interpretation approach based on displacement field to detect regions R that can distinguish AD and normal elder controls (NC)
Summary
Alzheimer’s disease (AD) is an abnormal process of aging. AD is a special category of senile dementia (SD) which leads to short-term and long-term memory, thinking, and behavior (Dong et al, 2015a). Research on AD has attracted scholars from all over the world because of its importance and effect on the society. How to cite this article Zhang and Wang (2015), Detection of Alzheimer’s disease by displacement field and machine learning. In 2006, more than twenty million people in the world suffered from this disease (Murphy et al, 2011). AD is predicted to influence 1 in every 85 people worldwide about thirty years later, and more than forty percent of prevalent cases need high level of care (Brookmeyer et al, 2007)
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
