Left vertical segmentation of 2-D heart MRI images using U-net network - Rachmat Rachmat; Kasmawaru Kasmawaru; Muh. Rafli R; Muh Yusuf; Muh Fahmi Basmar (Institute of Computer Science (IOCS), 2023)
Medical image processing has benefited greatly from advances in artificial intelligence, especially through the use of artificial neural networks. U-Net is an artificial neural network architecture that has proven successful in medical image segmentation tasks. Therefore, this study aims to combine the power of U-Net networks with 2-D cardiac MRI images to achieve accurate and automatic left vertical segmentation of the heart. By having a tool that can automatically segment the left vertical heart, doctors and researchers will be able to save valuable time in medical image analysis, while increasing accuracy and consistency in the assessment of heart structure. The results of this research will contribute to technological developments in the field of cardiovascular medicine and improve the care of patients with heart disease. Based on the work that was done and the results that were reported in Tabel I, the accuracy at the time of validation for full heart coroners, core heart coroners, and augmenting heart coroners was, respectively, 90.22%.