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Fuzzy Connectedness Based Segmentation of Fetal Heart from Clinical Ultrasound Images

Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 27)

Abstract

Congenital Heart Disease(CHD) is one among the most imperative causes of neonatal morbidity and mortality. Nearly 10 percentile of contemporary infant mortality in India is accounted for CHD. It is optimal to use ultrasound imaging modality for scanning the well-being of growing fetus owing to its non-invasive nature. But then several issues such as the manifestation of speckle noise, poor quality of ultrasound images with low signal to noise ratio and rapid movements of anatomically small fetal heart makes ultrasound prenatal diagnosis of cardiac defects as a most challenging task, which can only be done flawlessly by experienced radiologists. This paper demonstrates testing the method of fuzzy connectedness based image segmentation to detect the fetal heart structures from ultrasound image sequences. The proposed work involves Probabilistic Patch Based Maximum Likelihood Estimation(PPBMLE) based image denoising technique as a pre-processing step to remove the inherent speckle noise present in ultrasound images. The second step is use of Fuzzy connectedness based image segmentation algorithm with predefined seed points selected manually inside the fetal heart structure. The results of Matlab based simulation on fetal heart ultrasound dataset proves that the combination of above mentioned image processing techniques was predominantly successful in delineating the fetal heart structures. Quantitative results of the proposed work is apparently shown to illustrate the efficacy of the PPBMLE preprocessing technique.

Keywords

Speckle suppression Fuzzy connectedness Image segmentation Probabilistic patch based weights Maximum Likelihood Estimation 

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References

  1. 1.
    Hoffman, J.I., Kaplan, S.: The incidence of congenital heart disease. J. American College of Cardiology Foundation 147, 1890–1900 (2002)CrossRefGoogle Scholar
  2. 2.
    Rychik, J., Ayres, N., Cuneo, B., Spevak, P.J., Van Der Veld, M.: American Society of Echocardiography Guidelines and Standards for performance of the fetal Echocardiogram. Journal of the American Society of Echocardiography, 803–810 (July 2004)Google Scholar
  3. 3.
    Goodman, J.: Some fundamental properties of speckle. Journal of Optical Society, 1145–1150 (1976)Google Scholar
  4. 4.
    Deledalle, C.-A.: Loic Denis and Florence Tupin: Iterative Weighted Maximum Likelihood Denoising with Probabilistic Patch based weights. IEEE Trans. in Image Processing, 2661–2672 (December 2009)Google Scholar
  5. 5.
    Alvares, L., Mazorra, L.: Signal and Image Restoration using Shock Filters and anisotropic diffusion. SIAM Journal of Numerical Analysis, 590–695 (1994)Google Scholar
  6. 6.
    Meghoufel, A., Cloutier, G., Crevier-Denoix, N., de Guise, J.A.: Tissue Characterization of Equine Tendons with clinical B-Scan Images using a Shock filter thinning algorithm. IEEE Trans. on Medical Imaging, 596–605 (March 2011)Google Scholar
  7. 7.
    Udupa, J.K., Samarasekera, S.: Fuzzy connectedness and object definition: Theory, Algorithms and applications in image segmentation, Graphical models and image processing. Graphical Models and Image Processing 59(3), 246–261 (1996)CrossRefGoogle Scholar
  8. 8.
    Lassige, T.A., Benkeser, P.J., Fyfe, D., Sharma, S.: Comparison of septal defects in 2D and 3D echocardiography using active contour models. Computerized Medical Imaging and Graphics 6, 377–388 (2000)CrossRefGoogle Scholar
  9. 9.
    Dindoyal, I., Lambrou, T., Deng, J., Todd-Pokropek, A.: Level set snake algorithms on the fetal heart. In: 4th IEEE International Symposium on Biomedical Imaging, pp. 864–867 (April 2007)Google Scholar
  10. 10.
    Wagner, R.F., Smith, S.W., Sandrik, J.M., Lopez, H.: Statistics of speckle in ultrasound B-Scans. IEEE Transactions on Sonics and Ultrasonics 30(3), 156–163 (1983)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Dhirajlal Gandhi College of TechnologySalemIndia
  2. 2.Muthayammal Engineering CollegeRasipuramIndia

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