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Efficient workflow for automatic segmentation of the right heart based on 2D echocardiography

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Abstract

The present study aimed to present a workflow algorithm for automatic processing of 2D echocardiography images. The workflow was based on several sequential steps. For each step, we compared different approaches. Epicardial 2D echocardiography datasets were acquired during various open-chest beating-heart surgical procedures in three porcine hearts. We proposed a metric called the global index that is a weighted average of several accuracy coefficients, indices and the mean processing time. This metric allows the estimation of the speed and accuracy for processing each image. The global index ranges from 0 to 1, which facilitates comparison between different approaches. The second step involved comparison among filtering, sharpening and segmentation techniques. During the noise reduction step, we compared the median filter, total variation filter, bilateral filter, curvature flow filter, non-local means filter and mean shift filter. To clarify the endocardium borders of the right heart, we used the linear sharpen. Lastly, we applied watershed segmentation, clusterisation, region-growing, morphological segmentation, image foresting segmentation and isoline delineation. We assessed all the techniques and identified the most appropriate workflow for echocardiography image segmentation of the right heart. For successful processing and segmentation of echocardiography images with minimal error, we found that the workflow should include the total variation filter/bilateral filter, linear sharpen technique, isoline delineation/region-growing segmentation and morphological post-processing. We presented an efficient and accurate workflow for the precise diagnosis of cardiovascular diseases. We introduced the global index metric for image pre-processing and segmentation estimation.

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Funding

This study was supported by the Russian Federation Governmental Program ‘Nauka’ № 12.8205.2017/БЧ (Addition Number: 4.1769.ГЗБ.2017) and the Tomsk Polytechnic University Competitiveness Enhancement Programme Grant (TPU CEP-RIO-52/2017).

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Authors and Affiliations

  1. Medical Devices Design Laboratory, RASA Center in Tomsk, Tomsk Polytechnic University, Tomsk, Russia

    Viacheslav V. Danilov, Igor P. Skirnevskiy, Olga M. Gerget, Egor E. Shelomentcev & Dmitrii Yu. Kolpashchikov

  2. Cardiac Surgery Department, Boston Children’s Hospital, Boston, USA

    Nikolay V. Vasilyev

Authors
  1. Viacheslav V. Danilov
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  2. Igor P. Skirnevskiy
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  3. Olga M. Gerget
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  4. Egor E. Shelomentcev
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  5. Dmitrii Yu. Kolpashchikov
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  6. Nikolay V. Vasilyev
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Corresponding author

Correspondence to Nikolay V. Vasilyev.

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All authors declare that they have no conflict of interest.

Research involving human participants and animals

The animal experimental protocols were approved by the Boston Children’s Hospital Institutional Animal Care and Use Committee. All animals received humane care in accordance with the 1996 Guide for the Care and Use of Laboratory Animals recommended by the US National Institutes of Health. This paper does not contain any studies using human participants performed by any of the authors.

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Danilov, V.V., Skirnevskiy, I.P., Gerget, O.M. et al. Efficient workflow for automatic segmentation of the right heart based on 2D echocardiography. Int J Cardiovasc Imaging 34, 1041–1055 (2018). https://doi.org/10.1007/s10554-018-1314-4

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