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A Hybrid Method for Endocardial Contour Extraction of Right Ventricle in 4-Slices from 3D Echocardiography Dataset.

Dawood FA, Rahmat RW, Kadiman SB, Abdullah LN, Zamrin MD - Adv Bioinformatics (2014)

Bottom Line: Speckle noise reduction and contrast enhancement were implemented in Phase II as preprocessing tasks.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.It has been done by comparing the segmentation results of RV cavity based on endocardial contour extraction with the ground truth.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, College of Science, University of Baghdad, Baghdad, Iraq ; Department of Multimedia, Faculty of Computer Science and Information Technology, UPM, 43400 Serdang, Selangor, Malaysia.

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.

No MeSH data available.


Related in: MedlinePlus

The comparative analysis of RV cavity area measurements in 4-slices through complete cardiac cycle using automatic and manual methods.
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fig10: The comparative analysis of RV cavity area measurements in 4-slices through complete cardiac cycle using automatic and manual methods.

Mentions: Table 2 summarizes the comparison analysis for the proposed method performance using these four quantitative measures (RMSD, DSC, PTP, and PFP), which are presented in terms of Mean ± SD. It can be noted the set number 1 for all slices have the higher values of PFP among other dataset. In particular, slice 2 from this dataset has the maximum value 11.37 ± 6.30 of PFP. This result has been obtained due to inaccurate manual tracing for RV endocardial contour of some frames. For the overall dataset, the distance error of the RV endocardial contour in the paired manual-to-automatic by RMSD measure was 2.21 ± 0.35 (mm) and the RV cavity area has 87% similarity with DSC. The PTP results show that the proposed approach performs efficiently in all dataset with overall performance of 95%. The statistical comparative analysis with standard error bars for the RV cavity area measurements (in cm2) through 4-slices between the proposed method RA and the manual method RM is presented in Figure 10. Furthermore, the linear regression analysis between the two methods—manual and automatic is demonstrated in Figure 11. The total 3D echocardiography images used are 216 for RV area measurements in both method that indicated by blue circles. It can be noted for both methods, the spread of the values is relatively low, demonstrating that inaccurate segmentation results does not have much influence in the RV area measurements. It can also be seen from figure, the regression coefficient is good and the comparative analysis showed a close relationship (r = 0.92) between manual and automatic methods.


A Hybrid Method for Endocardial Contour Extraction of Right Ventricle in 4-Slices from 3D Echocardiography Dataset.

Dawood FA, Rahmat RW, Kadiman SB, Abdullah LN, Zamrin MD - Adv Bioinformatics (2014)

The comparative analysis of RV cavity area measurements in 4-slices through complete cardiac cycle using automatic and manual methods.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4209758&req=5

fig10: The comparative analysis of RV cavity area measurements in 4-slices through complete cardiac cycle using automatic and manual methods.
Mentions: Table 2 summarizes the comparison analysis for the proposed method performance using these four quantitative measures (RMSD, DSC, PTP, and PFP), which are presented in terms of Mean ± SD. It can be noted the set number 1 for all slices have the higher values of PFP among other dataset. In particular, slice 2 from this dataset has the maximum value 11.37 ± 6.30 of PFP. This result has been obtained due to inaccurate manual tracing for RV endocardial contour of some frames. For the overall dataset, the distance error of the RV endocardial contour in the paired manual-to-automatic by RMSD measure was 2.21 ± 0.35 (mm) and the RV cavity area has 87% similarity with DSC. The PTP results show that the proposed approach performs efficiently in all dataset with overall performance of 95%. The statistical comparative analysis with standard error bars for the RV cavity area measurements (in cm2) through 4-slices between the proposed method RA and the manual method RM is presented in Figure 10. Furthermore, the linear regression analysis between the two methods—manual and automatic is demonstrated in Figure 11. The total 3D echocardiography images used are 216 for RV area measurements in both method that indicated by blue circles. It can be noted for both methods, the spread of the values is relatively low, demonstrating that inaccurate segmentation results does not have much influence in the RV area measurements. It can also be seen from figure, the regression coefficient is good and the comparative analysis showed a close relationship (r = 0.92) between manual and automatic methods.

Bottom Line: Speckle noise reduction and contrast enhancement were implemented in Phase II as preprocessing tasks.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.It has been done by comparing the segmentation results of RV cavity based on endocardial contour extraction with the ground truth.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, College of Science, University of Baghdad, Baghdad, Iraq ; Department of Multimedia, Faculty of Computer Science and Information Technology, UPM, 43400 Serdang, Selangor, Malaysia.

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.

No MeSH data available.


Related in: MedlinePlus