Benchmark for Algorithms Segmenting the Left Atrium From 3D CT and MRI Datasets - Université de Rennes Access content directly
Journal Articles IEEE Transactions on Medical Imaging Year : 2015

Benchmark for Algorithms Segmenting the Left Atrium From 3D CT and MRI Datasets

Yefeng Zheng
  • Function : Author
  • PersonId : 836121
Maria A Zuluaga
Saïd Mahmoudi


Knowledge of left atrial (LA) anatomy is important for atrial fibrillation ablation guidance, fibrosis quantification and biophysical modelling. Segmentation of the LA from Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) images is a complex problem. This manuscript presents a benchmark to evaluate algorithms that address LA segmentation. The datasets, ground truth and evaluation code have been made publicly available through the website. This manuscript also reports the results of the Left Atrial Segmentation Challenge (LASC) carried out at the STACOM'13 workshop, in conjunction with MICCAI'13. Thirty CT and 30 MRI datasets were provided to participants for segmentation. Each participant segmented the LA including a short part of the LA appendage trunk and proximal sections of the pulmonary veins (PVs). We present results for nine algorithms for CT and eight algorithms for MRI. Results showed that methodologies combining statistical models with region growing approaches were the most appropriate to handle the proposed task. The ground truth and automatic segmentations were standardised to reduce the influence of inconsistently defined regions (e.g., mitral plane, PVs end points, LA appendage). This standardisation framework, which is a contribution of this work, can be used to label and further analyse anatomical regions of the LA. By performing the standardisation directly on the left atrial surface, we can process multiple input data, including meshes exported from different electroanatomical mapping systems
Fichier principal
Vignette du fichier
2015_tobongomez_lasc.pdf (5.29 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01260607 , version 1 (31-08-2020)



Catalina Tobon-Gomez, Arjan J. Geers, Jochen Peters, Jürgen Weese, Karen Pinto, et al.. Benchmark for Algorithms Segmenting the Left Atrium From 3D CT and MRI Datasets. IEEE Transactions on Medical Imaging, 2015, 34 (7), pp.1460--1473. ⟨10.1109/TMI.2015.2398818⟩. ⟨hal-01260607⟩
444 View
447 Download



Gmail Facebook Twitter LinkedIn More