Left Ventricle Segmentation in Cardiac MR: A Systematic Mapping of the Past Decade

Abstract

Left ventricle segmentation in short-axis cardiac magnetic resonance images is important to diagnose heart disease. However, the repetitive manual segmentation of these images requires considerable human effort and can decrease diagnostic accuracy. In recent years, several fully and semi-automatic approaches have been proposed, mainly using image-based, atlas, graphs, deformable models, and artificial intelligence methods. This paper presents a systematic mapping on the left ventricle segmentation, considering 74 studies published in the last decade. The main contributions of this review are: definition of the main segmentation challenges in these images; proposal of a new schematization, dividing the segmentation process into stages; categorization and analysis of the segmentation methods, including hybrid combinations; and analysis of the evaluation process, metrics, and databases. The performance of the methods in the most used public database is assessed, and the main limitations, weaknesses, and strengths of each method category are presented. Finally, trends, challenges, and research opportunities are discussed. The analysis indicates that methods from all categories can achieve good performance, and hybrid methods combining deep learning and deformable models obtain the best results. Methods still fail in specific slices, segment wrong regions, and produce anatomically impossible segmentations.

Segmentação do ventrículo esquerdo em exames de Ressonância Magnética Cardíaca com aprendizado profundo e modelos deformáveis contendo restrições de forma

“…Os métodos de segmentac ¸ão do VE em exames de RMC propostos na literatura podem ser divididos em cinco categorias [Ribeiro and Nunes 2022]: métodos clássicos de processamento de imagem (MCPI) [Hu et al 2019], atlas [Bai et al 2013], grafos [Yang et al 2016], MDs [Yang et al 2017a] e IA [Khened et al 2019]. Os métodos clássicos exploram técnicas como limiarizac ¸ão e extrac ¸ão de bordas.…”