Literature DB >> 21095747

Segmenting echocardiography images using B-Spline snake and active ellipse model.

Mahdi Marsousi1, Javad Alirezaie, Alireza Ahmadian, Armen Kocharian.   

Abstract

In this paper, a fully automated method for segmenting Left Ventricle (LV) in echocardiography images is proposed. A new method named active ellipse model is developed to automatically find the best ellipse inside the LV chamber without intervention of any specialist. A modified B-Spline Snake algorithm is used to segment the LV chamber in which the initial contour is formed by the predefined ellipse. As a result of using active ellipse model, the segmentation is extricated from dealing with gaps within myocardium boundary which are highly problematic in echocardiography image segmentation. Based on the results obtained from different studies, the proposed method is faster and more accurate than previous approaches. Our method is evaluated on 20 sets of echocardiography images of patients; and acquired results (92.30 ± 4.45% dice's coefficient) indicate the proposed method has remarkable performance.

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Year:  2010        PMID: 21095747     DOI: 10.1109/IEMBS.2010.5626094

Source DB:  PubMed          Journal:  Annu Int Conf IEEE Eng Med Biol Soc        ISSN: 2375-7477


  1 in total

Review 1.  Harnessing Machine Intelligence in Automatic Echocardiogram Analysis: Current Status, Limitations, and Future Directions.

Authors:  Ghada Zamzmi; Li-Yueh Hsu; Wen Li; Vandana Sachdev; Sameer Antani
Journal:  IEEE Rev Biomed Eng       Date:  2021-01-22
  1 in total

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