Tracking Anterior Mitral Leaflet in Echocardiographic Videos Using Morphological Operators and Active Contours

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2018

Autores

Sultan, MS (Autor) Outra; Martins, N (Autor) Outra; Costa, E (Autor) Outra; Veiga, D (Autor) Outra; Ferreira, MJA (Autor) Outra; Mattos, S (Autor) Outra; Coimbra, M (Autor) FCUP

Ata de Conferência Internacional

Título: BIOMEDICAL ENGINEERING SYSTEMS AND TECHNOLOGIES (BIOSTEC 2017)

Páginas: 146-162

10th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC)

Porto, PORTUGAL, FEB 21-23, 2017

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 0 Citações

Outras Informações

ID Authenticus: P-00P-1XC

DOI: 10.1007/978-3-319-94806-5_9

Abstract (EN): Rheumatic heart disease is the result of damage to the heart valves, more often the mitral valve. The heart valves leaflets get inflamed, scarred and stretched which interrupts the normal blood flow, resulting into serious health condition. Measuring and quantifying clinically relevant features, like thickness, mobility and shape can help to analyze the functionality of the valve, identify early cases of disease and reduce the disease burden. To obtain these features, the first step is to automatically delineate the relevant structures, such as the anterior mitral valve leaflet, throughout the echocardiographic video. In this work, we proposed a near real time method to track the anterior mitral leaflet in ultrasound videos using the parasternal long axis view. The method is semi-automatic, requiring a manual delineation of the anterior mitral leaflet in the first frame of the video. The method uses mathematical morphological techniques to obtain the rough boundaries of the leaflet and are further refined by the localized active contour framework. The mobility of the leaflet was also obtained, providing us the base to analyze the functionality of the valve (opening and closing). The algorithm was tested on 67 videos with 6432 frames. It outperformed with respect to the time consumption (0.4 s/frame), with the extended modified Hausdorff distance error of 3.7 pixels and the improved tracking performance (less failure).

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 17