Rodríguez Prado, Diego Vincent2019-10-042019-10-042019http://hdl.handle.net/10230/42385Treball de fi de grau en Sistemes AudiovisualsTutor: Karim LekadirNowadays machine learning models can be used to automate the process of cardiac segmentation, a tedious task usually done by cardiologists and radiologists to diagnose heart diseases and get insights of a certain patient’s heart. In this work, we propose combining state-of-the-art deep learning based models to automatically delineate cardiac MRI slices. By combining existing successful models—using both a stacking ensemble and a majority voting algorithm—we get similar or better results than the existing individual methods. In the experiments carried out, the ensemble methods outperform the original baseline models.application/pdfengAtribución-NoComercial-SinDerivadas 3.0 EspañaImatges tridimensionals en biologiaSistema cardiovascular -- MalaltiesAprenentatge automàticAutomatic cardiac segmentation by fusing deep learning modelsinfo:eu-repo/semantics/bachelorThesisinfo:eu-repo/semantics/openAccess