2026-04-13T08:14:41Zhttps://recercat.cat/oai/request

oai:recercat.cat:10230/423852025-12-25T19:56:59Zcom_2072_6col_2072_452954

urn:hdl:10230/42385 Automatic cardiac segmentation by fusing deep learning models Rodríguez Prado, Diego Vincent Imatges tridimensionals en biologia Sistema cardiovascular -- Malalties Aprenentatge automàtic Treball de fi de grau en Sistemes Audiovisuals Tutor: Karim Lekadir Nowadays 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. 2019-10-04T10:54:58Z 2019-10-04T10:54:58Z 2019 info:eu-repo/semantics/bachelorThesis Atribución-NoComercial-SinDerivadas 3.0 España http://creativecommons.org/licenses/by-nc-nd/3.0/es/ info:eu-repo/semantics/openAccess