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Authors: Malik Saad Sultan 1 ; Nelson Martins 2 ; Eva Costa 3 ; Diana Veiga 3 ; Manuel João Ferreira 4 ; Sandra Mattos 5 and Miguel Tavares Coimbra 1

Affiliations: 1 Universidade do Porto and Instituto de Telecomunicações, Portugal ; 2 Universidade do Porto, Instituto de Telecomunicações, Enermeter, Sistemas de Medição and Lda, Portugal ; 3 Enermeter, Sistemas de Medição and Lda, Portugal ; 4 Enermeter, Sistemas de Medição, Lda and University of Minho, Portugal ; 5 Circulo do Coração de Pernambuco, Brazil

ISBN: 978-989-758-215-8

Keyword(s): Ultrasound Images, Medical Image Processing, Active Contours, Segmentation and Tracking, Mitral Valve.

Related Ontology Subjects/Areas/Topics: Bioimaging ; Biomedical Engineering ; Image Processing Methods ; Medical Imaging and Diagnosis ; Ultrasound and Optical Imaging

Abstract: The mitral valve plays a vital role in our circulatory system. To study its functionality, it is important to measure clinically relevant parameters, such as its thickness, mobility and shape. Since manual segmentation is impractical, time consuming and requires expert knowledge, an automatic segmentation tool can have a significant clinical impact, providing objective measures to clinicians for understanding the morphology and behaviour of the mitral valve. In this work, a real time tracking method has been proposed for ultrasound videos obtained with the Parasternal Long Axis view. The algorithm is semi-automatic, assumes manual Anterior Mitral Leaflet segmentation in the first frame and then it uses mathematical morphology algorithms to obtain tracking results, further refined by localized active contours during the whole cardiac cycle. Finally, the medial axis is extracted for a quantitative analysis. Results show that the algorithm can segment 1137 frames extracted from 9 fully a nnotated sequences of the real clinical video data in only 0.89 sec/frame, with an average error of 5 pixels. Furthermore, the algorithms exhibited robust tracking performance in the most difficult situations, which are large frame-to-frame displacements. (More)

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Paper citation in several formats:
Sultan, M.; Martins, N.; Costa, E.; Veiga, D.; Ferreira, M.; Mattos, S. and Coimbra, M. (2017). Real-time Anterior Mitral Leaflet Tracking using Morphological Operators and Active Contours.In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2 BIOIMAGING: BIOIMAGING, (BIOSTEC 2017) ISBN 978-989-758-215-8, pages 39-46. DOI: 10.5220/0006244700390046

@conference{bioimaging17,
author={Malik Saad Sultan. and Nelson Martins. and Eva Costa. and Diana Veiga. and Manuel João Ferreira. and Sandra Mattos. and Miguel Tavares Coimbra.},
title={Real-time Anterior Mitral Leaflet Tracking using Morphological Operators and Active Contours},
booktitle={Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2 BIOIMAGING: BIOIMAGING, (BIOSTEC 2017)},
year={2017},
pages={39-46},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006244700390046},
isbn={978-989-758-215-8},
}

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2 BIOIMAGING: BIOIMAGING, (BIOSTEC 2017)
TI - Real-time Anterior Mitral Leaflet Tracking using Morphological Operators and Active Contours
SN - 978-989-758-215-8
AU - Sultan, M.
AU - Martins, N.
AU - Costa, E.
AU - Veiga, D.
AU - Ferreira, M.
AU - Mattos, S.
AU - Coimbra, M.
PY - 2017
SP - 39
EP - 46
DO - 10.5220/0006244700390046

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