Literature DB >> 19963714

Improved segmentation of echocardiographic images using fusion of images from different cardiac cycles.

Junier Caminha Amorim1, Maria do Carmo Dos Reis, Joao Luiz Azevedo de Carvalho, Adson Ferreira da Rocha, Juliana Fernandes Camapum.   

Abstract

In this work, an algorithm for the detection of the left ventricular border in two-dimensional long axis echocardiographic images is presented. In its preprocessing stage, images fusion was applied to a sequence of images composed of three cardiac cycles. This method exploits the similarity of corresponding frames from different cycles and produces contrast enhancement in the left ventricular boundary. This result improves the performance of the segmentation stage which is based on watershed transformation. The obtained left ventricle border is quantitatively and qualitatively compared with contours manually segmented by a cardiologist, and with results obtained using seven different techniques from the literature.

Mesh:

Year:  2009        PMID: 19963714     DOI: 10.1109/IEMBS.2009.5333101

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 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

2.  Semi-automatic algorithm for construction of the left ventricular area variation curve over a complete cardiac cycle.

Authors:  Salvador A Melo; Bruno Macchiavello; Marcelino M Andrade; João L A Carvalho; Hervaldo S Carvalho; Daniel F Vasconcelos; Pedro A Berger; Adson F da Rocha; Francisco A O Nascimento
Journal:  Biomed Eng Online       Date:  2010-01-15       Impact factor: 2.819

  2 in total

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