Benchmark for algorithms segmenting the left atrium from 3D CT and MRI datasets

Catalina Tobon-Gomez, Arjan Geers, Jochen Peters, Juergen Weese, Karen Pinto, Rashed Karim, Mohammed Ammar, Abdelaziz Daoudi, Jan Margeta, Zulma Sandoval, Birgit Stender, Yefeng Zheng, Maria A. Zuluaga, Julian Betancur, Nicholas Ayache, Mohammed Amine Chikh, Jean-Louis Dillenseger, B. Michael Kelm, Said Mahmoudi, Sebastien OurselinAlexander Schlaefer, Tobias Schaeffter, Reza Razavi, Kawal Rhode

Research output: Contribution to journalArticlepeer-review

144 Citations (Scopus)


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 standard-ised 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.

Original languageEnglish
Number of pages15
JournalIeee Transactions on Medical Imaging
Issue number99
Publication statusPublished - 3 Feb 2015


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