Classification of Alzheimer's Disease in MRI based on Dictionary Learning and Heavy Tailed Modelling.
Annu Int Conf IEEE Eng Med Biol Soc
; 2019: 454-457, 2019 Jul.
Article
em En
| MEDLINE
| ID: mdl-31945936
ABSTRACT
Diagnosis of brain diseases is considered one of the most challenging medical tasks to perform, even for medical experts who rely on high-resolution anatomical images to identify signs of abnormalities by visual inspection. However, new computational tools which assist to automate this diagnosis have the potential to significantly improve the speed and accuracy of this process. This work presents a model to aid in the task of classification of structural Magnetic Resonance Imaging scans. The classification is performed using a Support Vector Machine, whilst the features to analyze belong to a dictionary space. Such space was mainly built from a dictionary learning perspective, although a predefined one was also assessed. The results indicate that features learnt from the data of interest lead to improved classification performance. The proposed framework was tested on the ADNI dataset stage I.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Doença de Alzheimer
Limite:
Humans
Idioma:
En
Revista:
Annu Int Conf IEEE Eng Med Biol Soc
Ano de publicação:
2019
Tipo de documento:
Article