2026-04-13T05:02:25Zhttps://recercat.cat/oai/request

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

00925njm 22002777a 4500 dc Rodríguez Prado, Diego Vincent author 2019-10-04T10:54:58Z 2019-10-04T10:54:58Z 2019 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. Imatges tridimensionals en biologia Sistema cardiovascular -- Malalties Aprenentatge automàtic Automatic cardiac segmentation by fusing deep learning models