Efficient workflow for automatic segmentation of the right heart based on 2D echocardiography
| Autor: | Olga Gerget, Viacheslav Danilov, Egor E Shelomentcev, I. P. Skirnevskiy, Nikolay V. Vasilyev, Dmitrii Yu. Kolpashchikov |
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| Rok vydání: | 2018 |
| Předmět: |
Swine
Noise reduction Signal-To-Noise Ratio Workflow 030218 nuclear medicine & medical imaging Automation 03 medical and health sciences 0302 clinical medicine Image Processing Computer-Assisted Median filter Animals Medicine Radiology Nuclear Medicine and imaging Segmentation Mean-shift Cardiac Surgical Procedures Intraoperative Care business.industry Heart Pattern recognition Image segmentation Filter (signal processing) Echocardiography Models Animal Metric (mathematics) Bilateral filter Artificial intelligence Cardiology and Cardiovascular Medicine business Algorithms 030217 neurology & neurosurgery |
| Zdroj: | The International Journal of Cardiovascular Imaging. 34:1041-1055 |
| ISSN: | 1573-0743 1569-5794 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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