The Residual Center of Mass: An Image Descriptor for the Diagnosis of Alzheimer Disease

Author(s)

Yamashita, Alexandre Yukio ^[1] ; Falcao, Alexandre Xavier ^[2] ; Leite, Neucimar Jeronimo ^[2] ; Initia, Alzheimers Dis Neuroimaging

Affiliation

^[1] Inst Pesquisas Eldorado, Dept Software B, Campinas, SP - Brazil

^[2] Univ Estadual Campinas, Inst Comp, Campinas, SP - Brazil

• Document type: Journal article
• Source: NEUROINFORMATICS; v. 17, n. 2, p. 307-321, APR 2019.
• Web of Science Citations: 1

Abstract

A crucial quest in neuroimaging is the discovery of image features (biomarkers) associated with neurodegenerative disorders. Recent works show that such biomarkers can be obtained by image analysis techniques. However, these techniques cannot be directly compared since they use different databases and validation protocols. In this paper, we present an extensive study of image descriptors for the diagnosis of Alzheimer Disease (AD) and introduce a new one, named Residual Center of Mass (RCM). The RCM descriptor explores image moments and other techniques to enhance brain regions and select discriminative features for the diagnosis of AD. For validation, a Support Vector Machine (SVM) is trained with the selected features to classify images from normal subjects and patients with AD. We show that RCM with SVM achieves the best accuracies on a considerable number of exams by 10-fold cross-validation-95.1% on 507 FDG-PET scans and 90.3% on 1374 MRI scans. (AU)

• FAPESP's process: 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction?
• Grantee: Alexandre Xavier Falcão
• Support Opportunities: Research Projects - Thematic Grants