Self-supervised pretraining for transferable quantitative phase image cell segmentation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F21%3APU141672" target="_blank" >RIV/00216305:26220/21:PU141672 - isvavai.cz</a>
Alternative codes found
RIV/00216224:14110/21:00123919
Result on the web
<a href="https://www.osapublishing.org/boe/fulltext.cfm?uri=boe-12-10-6514&id=459853" target="_blank" >https://www.osapublishing.org/boe/fulltext.cfm?uri=boe-12-10-6514&id=459853</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1364/BOE.433212" target="_blank" >10.1364/BOE.433212</a>
Alternative languages
Result language
angličtina
Original language name
Self-supervised pretraining for transferable quantitative phase image cell segmentation
Original language description
In this paper, a novel U-Net-based method for robust adherent cell segmentation for quantitative phase microscopy image is designed and optimised. We designed and evaluated four specific post-processing pipelines. To increase the transferability to different cell types, non-deep learning transfer with adjustable parameters is used in the post-processing step. Additionally, we proposed a self-supervised pretraining technique using nonlabelled data, which is trained to reconstruct multiple image distortions and improved the segmentation performance from 0.67 to 0.70 of object-wise intersection over union. Moreover, we publish a new dataset of manually labelled images suitable for this task together with the unlabelled data for self-supervised pretraining.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
20601 - Medical engineering
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Biomedical Optics Express
ISSN
2156-7085
e-ISSN
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Volume of the periodical
12
Issue of the periodical within the volume
10
Country of publishing house
US - UNITED STATES
Number of pages
15
Pages from-to
6514-6528
UT code for WoS article
000703871700005
EID of the result in the Scopus database
2-s2.0-85115888948