Unsupervised machine learning exploration of morphological and haemodynamic indices to predict thrombus formation in the left atrial appendage

Springer This is a author's accepted manuscript of: Saiz-Vivó M, Mill JH, Jimenez-Pérez G, Legghe B, Iriart X, Cochet H, et al. Unsupervised machine learning exploration of morphological and haemodynamic indices to predict thrombus formation in the left atrial appendage. In: STACOM 2022: Statistical atlases and computational models of the heart. Regular and CMRxMotion challenge papers; 2022 Sep 18; Singapore. Cham: Springer; 2022. p. 200-10. DOI: 10.1007/978-3-031-23443-9_19 info:eu-repo/semantics/openAccess ;DOI: 10.1007/978-3-031-23443-9_19

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Sequential Segmentation of the Left Atrium and Atrial Scars Using a Multi-scale Weight Sharing Network and Boundary-Based Processing

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Sensitivity analysis of left atrial wall modeling approaches and inlet/outlet boundary conditions in fluid simulations to predict thrombus formation

Springer This is a author's accepted manuscript of: Albors C, Mill J, Kjeldsberg HA, Viladés Medel D; Olivares AL, et al.Sensitivity analysis of left atrial wall modeling approaches and inlet/outlet boundary conditions in fluid simulations to predict thrombus formation. In: STACOM 2022: Statistical atlases and computational models of the heart. Regular and CMRxMotion challenge papers; 2022 Sep 18; Singapore. Cham: Springer; 2022. p. 179–89. DOI: 978-3-031-23443-9_17 info:eu-repo/semantics/openAccess ;DOI: 10.1007/978-3-031-23443-9_17

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