CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
Reseach Article

Automatic Border Detection of the Left Ventricle in Parasternal Short Axis View of Echocardiogram

by G. N. Balaji, T. S. Subashini
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 77 - Number 12
Year of Publication: 2013
Authors: G. N. Balaji, T. S. Subashini
10.5120/13449-1348

G. N. Balaji, T. S. Subashini . Automatic Border Detection of the Left Ventricle in Parasternal Short Axis View of Echocardiogram. International Journal of Computer Applications. 77, 12 ( September 2013), 33-37. DOI=10.5120/13449-1348

@article{ 10.5120/13449-1348,
author = { G. N. Balaji, T. S. Subashini },
title = { Automatic Border Detection of the Left Ventricle in Parasternal Short Axis View of Echocardiogram },
journal = { International Journal of Computer Applications },
issue_date = { September 2013 },
volume = { 77 },
number = { 12 },
month = { September },
year = { 2013 },
issn = { 0975-8887 },
pages = { 33-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume77/number12/13449-1348/ },
doi = { 10.5120/13449-1348 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:49:00.573807+05:30
%A G. N. Balaji
%A T. S. Subashini
%T Automatic Border Detection of the Left Ventricle in Parasternal Short Axis View of Echocardiogram
%J International Journal of Computer Applications
%@ 0975-8887
%V 77
%N 12
%P 33-37
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Echocardiogram is one of the easiest ad widely employed methods that uses ultrasound to evaluate heart muscle, heart valves, and risk for heart disease. Heart failure (HF) can result from any structural or functional cardiac disorder that impairs the ability of the ventricle to fill with or eject blood. Echocardiography represents "the gold standard" in the assessment of left ventricle LV systolic and diastolic dysfunction. Left ventricular dimensions, volumes and wall thicknesses are echocardiographic measurements that are widely used in clinical practice and research. To obtain accurate linear measurements from the echocardiography accurate segmentation of the LV is essential. This paper proposes a method to segment the left ventricular border automatically on the 3-dimensional (2D+t) echocardiogram, where 't' is the time. The 2D image is obtained by extracting the frames from the video of echocardiogram which is further processed to detect the edges of the left ventricle and finally the edge detected frames are converted back into video which will help the cardiologist to visualize the left ventricle in motion. The obtained results are efficient and can be utilized for the purpose of detecting various medical parameters.

References
  1. Frazin L, Talano JV, Stephanides L, Loeb HS, Kopel L, Gunnar RM. Esophageal echocardiography. Circulation.
  2. Hisanaga K, Hisanaga A, Nagata K, Ichie Y. Transesophageal crosssectional echocardiography. Am Heart J 1980.
  3. Schluter M, Henrath P. Transesophageal echocardiography: potential advantages and initial clinical results. Practical Cardiol. . 1983;9:149.
  4. Omoto, Ryozo, et al. "The development of real-time two-dimensional Doppler echocardiography and its clinical significance in acquired valvular diseases. With special reference to the evaluation of valvular regurgitation. " Japanese heart journal 25. 3 (1984): 325-340.
  5. Strandness Jr, D. E. , et al. "Transcutaneous directional flow detection: A preliminary report. " American heart journal 78. 1 (1969): 554-556.
  6. Baker DW, Rubenstein SA, Lorch GS. Pulsed Doppler echocardiography principles and applications. Am J Med. . 1977; 63:69-80.
  7. S. Sudha, G. R. Suresh and R. Sukanesh Speckle Noise Reduction in Ultrasound Images by Wavelet Thresholding based on Weighted Variance, International Journal of Computer Theory and Engineering, Vol. 1, No. 1, April 2009.
  8. A. Mishra, P. K. Dutta, and M. K. Ghosh, A GA based approach for boundary detection of left ventricle with echocardiographic image sequences. Image Vis. Compute. , vol. 21, pp. 967-976, 2003.
  9. T. Loupas, W. N. Mcdicken, and P. L. Allan. An Adaptive Weighted Median Filter for Speckle Suppression in Medical Ultrasonic Images OO98-4094/89/01OO-012901 . 01 989 IEEE.
  10. Saulo Guerreiro Lacerda, Adson F. da Rocha, Daniel F. Vasconcelos,Joo L. A. de Carvalho, Iwens G. Sene Jr. and Juliana F. Camapum Left Ventricle Segmentation in Echocardiography Using a Radial-Search-Based Image Processing Algorithm. IEEE 2008.
  11. Sheila Chan, Gopalakrishnan Sainarayanan, Fuzzy-based boundary enhancement for echocardiogram using local image characteristics. Malaysian Journal of Computer Science, Vol. 19(2), 2006.
  12. Chu, C. H. , Delp, E. J. , and Buda, A. J. (1988). Detecting left ventricular endocardial and epicardial boundaries by digital two dimensional echocardiography. IEEE Transactions on Medical Imaging.
  13. Staib, L. H. , and Duncan, J. S. (1992). Boundary finding with parametrically deformable models. IEEE Transactions on Pattern Analys is and Machine Intelligence.
  14. Chalana, V. , Linker, D. T. , Haynor, D. R. , and Kim, Y. (1996). A multiple active contour model for cardiac boundary detection one echocardiographic sequences. IEEE Transactions on Medical Imaging,15, 290298.
  15. Kass M. , Witkin A. , and Terzopoulos D. (1988). Snakes: Active contour models. International Journal of Computer Vision, 1, 321331.
  16. Antonio Fernandez-Caballero, Jose M. Vega-Riesco. Determining heart parameters through left ventricular automatic segmentation for heart disease diagnosis. Expert Systems with Applications 36 (2009) 223422492007ElsevierLtd. All rights reserved doi:10. 1016/j. eswa. 2007. 12. 045.
  17. A Bosnjak, G Montilla, V Torrealba, Medical Images Segmentation using Gabor Filters applied to Echocardiographic Images0276-6547/981998 IEEE.
  18. IvanaMikic,* Slawomir Krucinski, and James D. Thomas, Segmentation and Tracking in Echocardiographic Sequences: Active Contours Guided by Optical Flow Estimates S 0278-0062(98)04883-6. 1998 IEEE.
  19. Jierong Cheng, Say Wei Foo, and Shankar M. Krishnan Watershed Presegmented Snake for Boundary Detection and Tracking of Left ventricle in Echocardiographic Images IEEE transactions on informationtechnology in biomedicine, vol. 10, no. 2, April 2006.
  20. S. Nandagopalan, C. Dhanalakshmi, Dr. B. S. Adiga N. Deepak, Automatic Segmentation and Ventricular Border Detection of 2DEchocardiographic Images Combining K-Means Clustering and Active Contour Model. IEEE 2010.
  21. R. c. Gonzanez and R. e woods DIP, Pearson education Singapore, 2002.
  22. Zhang F. ,Koh L. M. , Yoo Y. M. and Kim Y. ,2007, Nonlinear diffusion in Laplacian pyramid domain for ultrasonic speckle reduction, IEEE Trans. on Medical Imaging.
Index Terms

Computer Science
Information Sciences

Keywords

Echocardiogram Left ventricular automatic detection segmentation.