A hybrid method for endocardial contour extraction of right ventricle in 4-slices from 3D echocardiography dataset

Faten A. Dawood, Rahmita W. Rahmat, Suhaini B. Kadiman, Lili N. Abdullah, Mohd D. Zamrin

    Research output: Contribution to journalArticle

    1 Citation (Scopus)

    Abstract

    This paper presents a hybrid method to extract endocardial contour of the right ventricular (RV) in 4-slices from 3D echocardiography dataset. The overall framework comprises four processing phases. In Phase I, the region of interest (ROI) is identified by estimating the cavity boundary. Speckle noise reduction and contrast enhancement were implemented in Phase II as preprocessing tasks. In Phase III, the RV cavity region was segmented by generating intensity threshold which was used for once for all frames. Finally, Phase IV is proposed to extract the RV endocardial contour in a complete cardiac cycle using a combination of shape-based contour detection and improved radial search algorithm. The proposed method was applied to 16 datasets of 3D echocardiography encompassing the RV in long-axis view. The accuracy of experimental results obtained by the proposed method was evaluated qualitatively and quantitatively. It has been done by comparing the segmentation results of RV cavity based on endocardial contour extraction with the ground truth. The comparative analysis results show that the proposed method performs efficiently in all datasets with overall performance of 95% and the root mean square distances (RMSD) measure in terms of mean ± SD was found to be 2.21 ± 0.35 mm for RV endocardial contours.

    Original languageEnglish
    Article number207149
    JournalAdvances in Bioinformatics
    Volume2014
    DOIs
    Publication statusPublished - 2014

    Fingerprint

    Three-Dimensional Echocardiography
    Echocardiography
    Heart Ventricles
    Speckle
    Noise abatement
    Processing
    Datasets

    ASJC Scopus subject areas

    • Computer Science Applications
    • Biochemistry, Genetics and Molecular Biology (miscellaneous)
    • Biomedical Engineering

    Cite this

    A hybrid method for endocardial contour extraction of right ventricle in 4-slices from 3D echocardiography dataset. / Dawood, Faten A.; Rahmat, Rahmita W.; Kadiman, Suhaini B.; Abdullah, Lili N.; Zamrin, Mohd D.

    In: Advances in Bioinformatics, Vol. 2014, 207149, 2014.

    Research output: Contribution to journalArticle

    Dawood, Faten A. ; Rahmat, Rahmita W. ; Kadiman, Suhaini B. ; Abdullah, Lili N. ; Zamrin, Mohd D. / A hybrid method for endocardial contour extraction of right ventricle in 4-slices from 3D echocardiography dataset. In: Advances in Bioinformatics. 2014 ; Vol. 2014.
    @article{1697c5e3f06d46aa8ba0f4448b9b271a,
    title = "A hybrid method for endocardial contour extraction of right ventricle in 4-slices from 3D echocardiography dataset",
    abstract = "This paper presents a hybrid method to extract endocardial contour of the right ventricular (RV) in 4-slices from 3D echocardiography dataset. The overall framework comprises four processing phases. In Phase I, the region of interest (ROI) is identified by estimating the cavity boundary. Speckle noise reduction and contrast enhancement were implemented in Phase II as preprocessing tasks. In Phase III, the RV cavity region was segmented by generating intensity threshold which was used for once for all frames. Finally, Phase IV is proposed to extract the RV endocardial contour in a complete cardiac cycle using a combination of shape-based contour detection and improved radial search algorithm. The proposed method was applied to 16 datasets of 3D echocardiography encompassing the RV in long-axis view. The accuracy of experimental results obtained by the proposed method was evaluated qualitatively and quantitatively. It has been done by comparing the segmentation results of RV cavity based on endocardial contour extraction with the ground truth. The comparative analysis results show that the proposed method performs efficiently in all datasets with overall performance of 95{\%} and the root mean square distances (RMSD) measure in terms of mean ± SD was found to be 2.21 ± 0.35 mm for RV endocardial contours.",
    author = "Dawood, {Faten A.} and Rahmat, {Rahmita W.} and Kadiman, {Suhaini B.} and Abdullah, {Lili N.} and Zamrin, {Mohd D.}",
    year = "2014",
    doi = "10.1155/2014/207149",
    language = "English",
    volume = "2014",
    journal = "Advances in Bioinformatics",
    issn = "1687-8027",
    publisher = "Hindawi Publishing Corporation",

    }

    TY - JOUR

    T1 - A hybrid method for endocardial contour extraction of right ventricle in 4-slices from 3D echocardiography dataset

    AU - Dawood, Faten A.

    AU - Rahmat, Rahmita W.

    AU - Kadiman, Suhaini B.

    AU - Abdullah, Lili N.

    AU - Zamrin, Mohd D.

    PY - 2014

    Y1 - 2014

    N2 - This paper presents a hybrid method to extract endocardial contour of the right ventricular (RV) in 4-slices from 3D echocardiography dataset. The overall framework comprises four processing phases. In Phase I, the region of interest (ROI) is identified by estimating the cavity boundary. Speckle noise reduction and contrast enhancement were implemented in Phase II as preprocessing tasks. In Phase III, the RV cavity region was segmented by generating intensity threshold which was used for once for all frames. Finally, Phase IV is proposed to extract the RV endocardial contour in a complete cardiac cycle using a combination of shape-based contour detection and improved radial search algorithm. The proposed method was applied to 16 datasets of 3D echocardiography encompassing the RV in long-axis view. The accuracy of experimental results obtained by the proposed method was evaluated qualitatively and quantitatively. It has been done by comparing the segmentation results of RV cavity based on endocardial contour extraction with the ground truth. The comparative analysis results show that the proposed method performs efficiently in all datasets with overall performance of 95% and the root mean square distances (RMSD) measure in terms of mean ± SD was found to be 2.21 ± 0.35 mm for RV endocardial contours.

    AB - This paper presents a hybrid method to extract endocardial contour of the right ventricular (RV) in 4-slices from 3D echocardiography dataset. The overall framework comprises four processing phases. In Phase I, the region of interest (ROI) is identified by estimating the cavity boundary. Speckle noise reduction and contrast enhancement were implemented in Phase II as preprocessing tasks. In Phase III, the RV cavity region was segmented by generating intensity threshold which was used for once for all frames. Finally, Phase IV is proposed to extract the RV endocardial contour in a complete cardiac cycle using a combination of shape-based contour detection and improved radial search algorithm. The proposed method was applied to 16 datasets of 3D echocardiography encompassing the RV in long-axis view. The accuracy of experimental results obtained by the proposed method was evaluated qualitatively and quantitatively. It has been done by comparing the segmentation results of RV cavity based on endocardial contour extraction with the ground truth. The comparative analysis results show that the proposed method performs efficiently in all datasets with overall performance of 95% and the root mean square distances (RMSD) measure in terms of mean ± SD was found to be 2.21 ± 0.35 mm for RV endocardial contours.

    UR - http://www.scopus.com/inward/record.url?scp=84908341342&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84908341342&partnerID=8YFLogxK

    U2 - 10.1155/2014/207149

    DO - 10.1155/2014/207149

    M3 - Article

    AN - SCOPUS:84908341342

    VL - 2014

    JO - Advances in Bioinformatics

    JF - Advances in Bioinformatics

    SN - 1687-8027

    M1 - 207149

    ER -