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Mathematical Methodologies in Pattern Recognition and Machine Learning pp 163–178Cite as

A Robust Deformable Model for 3D Segmentation of the Left Ventricle from Ultrasound Data

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Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 30))

Abstract

This paper presents a novel bottom-up deformable-based model for the segmentation of the Left Ventricle (LV) in 3D ultrasound data. The methodology presented here is based on Probabilistic Data Association Filter (PDAF). The main steps that characterize the proposed approach can be summarized as follows. After a rough initialization given by the user, the following steps are performed: (1) low-level transition edge points are detected based on a prior model for the intensity of the LV, (2) middle-level features or patch formation is accomplished by linking the low-level information, (3) data interpretations are computed (hypothesis) based on the reliability (belonging or not to the LV boundary) of the previously obtained patches, (4) a confidence degree is assigned to each data interpretation and the model is updated taking into account all data interpretations.Results testify the usefulness of the approach in both synthetic and real LV volumes data. The obtained LV segmentations are compared with expert’s manual segmentations, yielding an average distance of 3 mm between them.

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Acknowledgements

This work was supported by project [PTDC/EEA-CRO/103462/2008] (project HEARTRACK) and FCT [PEst-OE/EEI/LA0009/2011].

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Authors and Affiliations

  1. Institute for Systems and Robotics, Instituto Superior Tecnico, Lisbon, Portugal

    Carlos Santiago, Jorge S. Marques & Jacinto C. Nascimento

Authors
  1. Carlos Santiago
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  2. Jorge S. Marques
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  3. Jacinto C. Nascimento
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Corresponding author

Correspondence to Carlos Santiago .

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Editors and Affiliations

  1. , Dpt. Lenguajes y Sistemas Informáticos, Jaume I University, Campus del Riu Sec s/n, Castellón de la Plana, 12071, Spain

    Pedro Latorre Carmona

  2. , Dpt. Lenguajes y Sistemas Informáticos, Jaume I University, Campus del Riu Sec s/n, Castellón de la Plana, 12071, Spain

    J. Salvador Sánchez

  3. Technical University of Lisbon, Av. Rovisco Pais, Torre Norte, piso 10, Lisbon, 1049-001, Portugal

    Ana L.N. Fred

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Santiago, C., Marques, J.S., Nascimento, J.C. (2013). A Robust Deformable Model for 3D Segmentation of the Left Ventricle from Ultrasound Data. In: Latorre Carmona, P., Sánchez, J., Fred, A. (eds) Mathematical Methodologies in Pattern Recognition and Machine Learning. Springer Proceedings in Mathematics & Statistics, vol 30. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-5076-4_11

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