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Mitral valve disease is a commonly occurring pathology and its incidence is expected to rise in the coming decades. This has led to an increase in the number and complexity of computational models developed to characterize the mitral valve behaviour, resulting in the need for automated segmentation methods. In this study, we evaluated the suitability of particle systems for segmenting the mitral valve leaflets from 3D TOE images, for both systolic and diastolic phases. With a mean error of 0.77 ± 0.4 mm, our approach results in accurate medial surface representations of the mitral valve. Additionally, we investigated the correlation between particle strength and leaflet thickness. Although a thorough analysis is still required to fully establish this relation, our preliminary results, with a mean RMS error of 0.99 ± 0.27 mm, show that leaflet thickness can be linked to particle strength. We anticipate that particle systems can be of high relevance for the generation of realistic patient-specific computational models, contributing to the development of adequate treatment strategies for mitral valve patients.

Using particle systems for mitral valve segmentation from 3D transoesophageal echocardiography (3D TOE) - a proof of concept