Diagnóstico da doença de Alzheimer usando autoencoders aplicados a imagens de ressonância magnética - Grivol, Marco Antônio Bernardi (Universidade Federal de São Carlos, 2022)
Alzheimer's disease (AD) is a neurodegenerative disease that causes damage associated with memory and thinking, causing a gradual decline in judgment, reasoning and learning. One of the ways to aid in the diagnosis of AD is the analysis of structural magnetic resonance (MR) images of the patient. Recent studies use computer vision, image processing and machine learning techniques to help diagnose AD. This work aims to extract features from MR images with stacked autoencoders and stacked convolutional autoencoders, and classify MR images via XGBoost into cognitively normal (CN) and AD classes. This work also compares Mean Squared Error (MSE) and Structural Similarity Index (SSIM) metrics as loss functions in autoencoders.
Diagnosis of Alzheimer's disease using autoencoders applied to magnetic resonance images
Keywords: Alzheimer; Imagens de ressonância magnética; Hipocampo; Autoencoders; Alzheimer's disease; Magnetic resonance images; XGBoost; Hippocampus; CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::METODOLOGIA E TECNICAS DA COMPUTACAO; CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO; ENGENHARIAS::ENGENHARIA BIOMEDICA::ENGENHARIA MEDICA