Automatic computational scheme for the detection, identification and classificatio...
| Grant number: | 18/09972-9 |
| Support type: | Scholarships in Brazil - Scientific Initiation |
| Effective date (Start): | December 01, 2018 |
| Effective date (End): | November 30, 2019 |
| Field of knowledge: | Physical Sciences and Mathematics - Computer Science |
| Principal Investigator: | Ricardo José Ferrari |
| Grantee: | Italo Antonio Duarte de Oliveira |
| Home Institution: | Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil |
Abstract Dementia has become one of the most significant public health problems worldwide due to the growing ageing of the elderly population. Among the different types of dementia, Alzheimer's disease (AD) is the most frequent, corresponding to almost 60% of the cases. According to the World Health Organization, the number of people with AD worldwide in 2010 was about 35.6 million and is estimated to nearly double by 2030 (65.7 million) and quadruple by 2050 (115.4 million). In Brazil, about one million people have already been affected by this disease. However, even when patients report symptoms and have visible signs of cognitive losses, dementia may not be diagnosed in time. In this scenario, the development of automatic computational techniques, both for diagnostic assistance and to elucidate uninvestigated elements about this disease, is essential for the search for the cure. Therefore, this research aims to develop techniques for the detection and subsequent analysis of asymmetries between the left and right hippocampal regions of magnetic resonance imaging (MRI) aiming at the classification of MRI images in the healthy and AD cognitive ageing classes. | |