Deep learning for hippocampus segmentation

• Grant number: 18/00186-0
• Support Opportunities: Scholarships in Brazil - Master
• Start date: October 01, 2018
• End date: June 30, 2020
• Field of knowledge: Engineering - Electrical Engineering
• Agreement: Coordination of Improvement of Higher Education Personnel (CAPES)
• Principal Investigator: Roberto de Alencar Lotufo
• Grantee: Diedre Santos do Carmo
• Host Institution: Faculdade de Engenharia Elétrica e de Computação (FEEC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 13/07559-3 - BRAINN - The Brazilian Institute of Neuroscience and Neurotechnology, AP.CEPID

Abstract

Hippocampus segmentation plays a key role in diagnosing various brain disorders such as Alzheimer's disease, epilepsy, multiple sclerosis, cancer, depression and others. Nowadays, segmentation is still mainly performed manually by experts. Segmentation done by experts is considered to be a gold-standard when evaluating automated methods, buts it is a time consuming and hard task, requiring specialized personnel.Recently effort has been done to achieve reliable automated segmentation. Currently, the best performing methods are multi atlas based with around 90\% DICE coefficient and very time consuming. Deep learning, a learning technique that is being used in many computer vision applications with great success, is still not very well studied in hippocampus segmentation, with some works recently starting to employ it on this particular segmentation problem.This M.Sc. research project intends to investigate the use of Deep Learning techniques applied to hippocampus segmentation in MR imaging. Our method aims to use the Simultaneous Truth andPerformance Level Estimation (STAPLE) algorithm to generate labeled data as a silver-standard and use it as input for a Convolutional Neural Network (CNN). We will compare our methodology with the state-of-the-art techniques for hippocampus segmentation.

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

CARMO, DIEDRE; SILVA, BRUNA; YASUDA, CLARISSA; RITTNER, LETICIA; LOTUFO, ROBERTO; NEUROIMAGING, ALZHEIMER'S DIS. Hippocampus segmentation on epilepsy and Alzheimer's disease studies with multiple convolutional neural networks. HELIYON, v. 7, n. 2, FEB 2021. (18/00186-0)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

CARMO, Diedre Santos do. Aprendizado profundo para segmentação do hipocampo. 2020. Master's Dissertation - Universidade Estadual de Campinas (UNICAMP). Faculdade de Engenharia Elétrica e de Computação Campinas, SP.