Abstract
Analyzing the structure of the left atrium can provide precious insights into the pathology of atrial fibrillation, eventually resulting in optimization of treatment plans. In this paper, an interactive and patient-specific method is presented to segment the left atrial endocardium(We refer to the segmentation of the region inside the left atrial endocardium as the segmentation of the left atrial endocardium, the same for epicardium.), the left atrial epicardium and measure the left atrial wall thickness from cardiac computed tomography images. A region growing algorithm was adapted to segment the left atrial endocardium, whereas the left atrial epicardium was segmented indirectly: a marker-controlled geodesic active contour model was defined on its surrounding environment. The results of the left atrial wall thickness were then mapped onto meshes generated from the endocardium segmentation. We tested our pipeline on 10 datasets as a part of the STACOM 2016 Left Atrial Wall Segmentation Challenge and we compared our method with manual segmentation. Aimed at facilitating the segmentation of the left atrial thin-wall structure, this pipeline is partially implemented in MUSIC software for clinical use. The expertise of clinicians can be added through the choice of specific parameters for each patient, although this remains optional owing to the robustness of the approach.
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Notes
- 1.
For step 1, polygons were drawn manually on a dozen of slices for each case and then interpolated automatically on the rest. Images are shown in axial planes.
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Acknowledgments
Part of the research was funded by the Agence Nationale de la Recherche (ANR)/ERA CoSysMed SysAFib and ANR MIGAT projects. The authors would like to thank Marc-Michel Rohé and Hervé Delingette for their constructive feedback and Inria dtk team (Nicolas Schnitzler and Thibaud Kloczko) for helping in implementing the pipeline.
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Jia, S., Cadour, L., Cochet, H., Sermesant, M. (2017). STACOM-SLAWT Challenge: Left Atrial Wall Segmentation and Thickness Measurement Using Region Growing and Marker-Controlled Geodesic Active Contour. In: Mansi, T., McLeod, K., Pop, M., Rhode, K., Sermesant, M., Young, A. (eds) Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges. STACOM 2016. Lecture Notes in Computer Science(), vol 10124. Springer, Cham. https://doi.org/10.1007/978-3-319-52718-5_23
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