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In vitro monitoring of photoinduced necrosis in HeLa cells using digital holographic microscopy and machine learning. / Belashov, A. V.; Zhikhoreva, A. A.; Belyaeva, T. N.; Kornilova, E. S.; Salova, A. V.; Semenova, I. V.; Vasyutinskii, O. S.

In: Journal of the Optical Society of America A: Optics and Image Science, and Vision, Vol. 37, No. 2, 2020, p. 346-352.

Research output: Contribution to journal › Article › peer-review

Harvard

Belashov, AV, Zhikhoreva, AA, Belyaeva, TN, Kornilova, ES, Salova, AV, Semenova, IV & Vasyutinskii, OS 2020, 'In vitro monitoring of photoinduced necrosis in HeLa cells using digital holographic microscopy and machine learning', Journal of the Optical Society of America A: Optics and Image Science, and Vision, vol. 37, no. 2, pp. 346-352. https://doi.org/10.1364/JOSAA.382135

APA

Belashov, A. V., Zhikhoreva, A. A., Belyaeva, T. N., Kornilova, E. S., Salova, A. V., Semenova, I. V., & Vasyutinskii, O. S. (2020). In vitro monitoring of photoinduced necrosis in HeLa cells using digital holographic microscopy and machine learning. Journal of the Optical Society of America A: Optics and Image Science, and Vision, 37(2), 346-352. https://doi.org/10.1364/JOSAA.382135

Vancouver

Belashov AV, Zhikhoreva AA, Belyaeva TN, Kornilova ES, Salova AV, Semenova IV et al. In vitro monitoring of photoinduced necrosis in HeLa cells using digital holographic microscopy and machine learning. Journal of the Optical Society of America A: Optics and Image Science, and Vision. 2020;37(2):346-352. https://doi.org/10.1364/JOSAA.382135

Author

Belashov, A. V. ; Zhikhoreva, A. A. ; Belyaeva, T. N. ; Kornilova, E. S. ; Salova, A. V. ; Semenova, I. V. ; Vasyutinskii, O. S. / In vitro monitoring of photoinduced necrosis in HeLa cells using digital holographic microscopy and machine learning. In: Journal of the Optical Society of America A: Optics and Image Science, and Vision. 2020 ; Vol. 37, No. 2. pp. 346-352.

BibTeX

@article{c66ae7d107d248dba57f42cc163c42d4,
title = "In vitro monitoring of photoinduced necrosis in HeLa cells using digital holographic microscopy and machine learning",
abstract = "Digital holographic microscopy supplemented with the developed cell segmentation and machine learning and classification algorithms is implemented for quantitative description of the dynamics of cellular necrosis induced by photodynamic treatment in vitro. It is demonstrated that the developed algorithms operating with a set of optical, morphological, and physiological parameters of cells, obtained from their phase images, can be used for automatic distinction between live and necrotic cells. The developed classifier provides high accuracy of about 95.5% and allows for calculation of survival rates in the course of cell death.",
author = "Belashov, {A. V.} and Zhikhoreva, {A. A.} and Belyaeva, {T. N.} and Kornilova, {E. S.} and Salova, {A. V.} and Semenova, {I. V.} and Vasyutinskii, {O. S.}",
note = "Publisher Copyright: {\textcopyright} 2020 Optical Society of America. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.",
year = "2020",
doi = "10.1364/JOSAA.382135",
language = "English",
volume = "37",
pages = "346--352",
journal = "Journal of the Optical Society of America A: Optics and Image Science, and Vision",
issn = "1084-7529",
publisher = "The Optical Society",
number = "2",

}

RIS

TY - JOUR

T1 - In vitro monitoring of photoinduced necrosis in HeLa cells using digital holographic microscopy and machine learning

AU - Belashov, A. V.

AU - Zhikhoreva, A. A.

AU - Belyaeva, T. N.

AU - Kornilova, E. S.

AU - Salova, A. V.

AU - Semenova, I. V.

AU - Vasyutinskii, O. S.

N1 - Publisher Copyright: © 2020 Optical Society of America. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020

Y1 - 2020

N2 - Digital holographic microscopy supplemented with the developed cell segmentation and machine learning and classification algorithms is implemented for quantitative description of the dynamics of cellular necrosis induced by photodynamic treatment in vitro. It is demonstrated that the developed algorithms operating with a set of optical, morphological, and physiological parameters of cells, obtained from their phase images, can be used for automatic distinction between live and necrotic cells. The developed classifier provides high accuracy of about 95.5% and allows for calculation of survival rates in the course of cell death.

AB - Digital holographic microscopy supplemented with the developed cell segmentation and machine learning and classification algorithms is implemented for quantitative description of the dynamics of cellular necrosis induced by photodynamic treatment in vitro. It is demonstrated that the developed algorithms operating with a set of optical, morphological, and physiological parameters of cells, obtained from their phase images, can be used for automatic distinction between live and necrotic cells. The developed classifier provides high accuracy of about 95.5% and allows for calculation of survival rates in the course of cell death.

UR - http://www.scopus.com/inward/record.url?scp=85078898013&partnerID=8YFLogxK

U2 - 10.1364/JOSAA.382135

DO - 10.1364/JOSAA.382135

M3 - Article

C2 - 32118916

AN - SCOPUS:85078898013

VL - 37

SP - 346

EP - 352

JO - Journal of the Optical Society of America A: Optics and Image Science, and Vision

JF - Journal of the Optical Society of America A: Optics and Image Science, and Vision

SN - 1084-7529

IS - 2

ER -

ID: 76657057