Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Moon, Inkyu | - |
dc.contributor.author | Jaferzadeh, Keyvan | - |
dc.contributor.author | Ahmadzadeh, Ezat | - |
dc.contributor.author | Javidi, Bahram | - |
dc.date.accessioned | 2018-10-30T05:59:28Z | - |
dc.date.available | 2018-10-30T05:59:28Z | - |
dc.date.created | 2018-10-15 | - |
dc.date.issued | 2018-12 | - |
dc.identifier.issn | 1864-063X | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11750/9371 | - |
dc.description.abstract | Cardiomyocytes derived from human pluripotent stem cells are a promising tool for disease modeling, drug compound testing, and cardiac toxicity screening. Bio-image segmentation is a prerequisite step in cardiomyocyte image analysis by digital holography (DH) in microscopic configuration and has provided satisfactory results. In this study, we quantified multiple cardiac cells from segmented 3-dimensional DH images at the single-cell level and measured multiple parameters describing the beating profile of each individual cell. The beating profile is extracted by monitoring dry-mass distribution during the mechanical contraction-relaxation activity caused by cardiac action potential. We present a robust two-step segmentation method for cardiomyocyte low-contrast image segmentation based on region and edge information. The segmented single-cell contains mostly the nucleus of the cell since it is the best part of the cardiac cell, which can be perfectly segmented. Clustering accuracy was assessed by a silhouette index evaluation for k-means clustering and the Dice similarity coefficient (DSC) of the final segmented image. 3D representation of single of cardiomyocytes. The cell contains mostly the nucleus section and a small area of cytoplasm. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim | - |
dc.language | English | - |
dc.publisher | Wiley - VCH Verlag GmbH & CO. KGaA | - |
dc.title | Automated quantitative analysis of multiple cardiomyocytes at the single-cell level with three-dimensional holographic imaging informatics | - |
dc.type | Article | - |
dc.identifier.doi | 10.1002/jbio.201800116 | - |
dc.identifier.scopusid | 2-s2.0-85053934672 | - |
dc.identifier.bibliographicCitation | Journal of Biophotonics, v.11, no.12, pp.1 - 12 | - |
dc.description.isOpenAccess | FALSE | - |
dc.subject.keywordAuthor | 3-dimensional image processing | - |
dc.subject.keywordAuthor | cardiac single-cell analysis | - |
dc.subject.keywordAuthor | cardiomyocyte image segmentation | - |
dc.subject.keywordAuthor | digital holographic cell imaging | - |
dc.subject.keywordPlus | MEANS CLUSTERING-ALGORITHM | - |
dc.subject.keywordPlus | RED-BLOOD-CELLS | - |
dc.subject.keywordPlus | SEGMENTATION | - |
dc.subject.keywordPlus | MICROSCOPY | - |
dc.citation.endPage | 12 | - |
dc.citation.number | 12 | - |
dc.citation.startPage | 1 | - |
dc.citation.title | Journal of Biophotonics | - |
dc.citation.volume | 11 | - |
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