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Computation 2016, 4(3), 35; doi:10.3390/computation4030035

Image Segmentation for Cardiovascular Biomedical Applications at Different Scales

1
Institute of Numerical Mathematics, Russian Academy of Sciences, Gubkina 8, 119333 Moscow, Russia
2
Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, Leninskie Gory 1, 119991 Moscow, Russia
*
Author to whom correspondence should be addressed.
Academic Editors: Gennady Bocharov, Olga Solovyova and Vitaly Volpert
Received: 30 June 2016 / Revised: 27 August 2016 / Accepted: 5 September 2016 / Published: 15 September 2016
(This article belongs to the Special Issue Multiscale and Hybrid Modeling of the Living Systems)
View Full-Text   |   Download PDF [3302 KB, uploaded 15 September 2016]   |  

Abstract

In this study, we present several image segmentation techniques for various image scales and modalities. We consider cellular-, organ-, and whole organism-levels of biological structures in cardiovascular applications. Several automatic segmentation techniques are presented and discussed in this work. The overall pipeline for reconstruction of biological structures consists of the following steps: image pre-processing, feature detection, initial mask generation, mask processing, and segmentation post-processing. Several examples of image segmentation are presented, including patient-specific abdominal tissues segmentation, vascular network identification and myocyte lipid droplet micro-structure reconstruction. View Full-Text
Keywords: image segmentation; abdominal tissues; coronary arteries; cerebral arteries; electron microscopy; cardiovascular applications image segmentation; abdominal tissues; coronary arteries; cerebral arteries; electron microscopy; cardiovascular applications
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Danilov, A.; Pryamonosov, R.; Yurova, A. Image Segmentation for Cardiovascular Biomedical Applications at Different Scales. Computation 2016, 4, 35.

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