Publication detail

Self-supervised pretraining for transferable quantitative phase image cell segmentation

VIČAR, T. CHMELÍK, J. JAKUBÍČEK, R. CHMELÍKOVÁ, L. GUMULEC, J. BALVAN, J. PROVAZNÍK, I. KOLÁŘ, R.

Original Title

Self-supervised pretraining for transferable quantitative phase image cell segmentation

Type

journal article in Web of Science

Language

English

Original Abstract

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.

Keywords

cell segmentation, deep learning, transfer learning, self-supervised

Authors

VIČAR, T.; CHMELÍK, J.; JAKUBÍČEK, R.; CHMELÍKOVÁ, L.; GUMULEC, J.; BALVAN, J.; PROVAZNÍK, I.; KOLÁŘ, R.

Released

24. 9. 2021

Publisher

Optica Publishing Group

Location

2010 MASSACHUSETTS AVE NW, WASHINGTON, DC 20036

ISBN

2156-7085

Periodical

Biomedical Optics Express

Year of study

12

Number

10

State

United States of America

Pages from

6514

Pages to

6528

Pages count

15

URL

https://www.osapublishing.org/boe/fulltext.cfm?uri=boe-12-10-6514&id=459853

Full text in the Digital Library

http://hdl.handle.net/11012/201741

BibTex

@article{BUT172596,
  author="Tomáš {Vičar} and Jiří {Chmelík} and Roman {Jakubíček} and Larisa {Chmelíková} and Jaromír {Gumulec} and Jan {Balvan} and Valentýna {Provazník} and Radim {Kolář}",
  title="Self-supervised pretraining for transferable quantitative phase image cell segmentation",
  journal="Biomedical Optics Express",
  year="2021",
  volume="12",
  number="10",
  pages="6514--6528",
  doi="10.1364/BOE.433212",
  issn="2156-7085",
  url="https://www.osapublishing.org/boe/fulltext.cfm?uri=boe-12-10-6514&id=459853"
}