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VIČAR, T. CHMELÍK, J. KOLÁŘ, R.
Original Title
Cell Segmentation in Quantitative Phase Images with Improved Iterative Thresholding Method
Type
conference paper
Language
English
Original Abstract
Quantitative Phase Imaging (QPI) is a label-free microscopic technique, which provides images with high contrast, moreover, it provides quantitative cell mass measurements for each pixel. Segmentation of particular cells is an important step in the analysis of QPI image data. This paper presents a method for automatic cell segmentation in QPI images. The proposed method improves iterative thresholding, which is a very promising method, however, it is not able to segment densely clustered cells. Our improved iterative thresholding includes two additional steps -- Laplacian of Gaussian image enhancement and distance transform-based splitting. The method was compared with original iterative thresholding and another method on two cell lines, where the proposed method successfully deals with a densely clustered type of cells and achieves significantly better results on both datasets
Keywords
Cell segmentation, Quantitative Phase Imaging, Iterative thresholding, Laplacian of Gaussian
Authors
VIČAR, T.; CHMELÍK, J.; KOLÁŘ, R.
Released
30. 11. 2020
Publisher
Springer Nature Switzerland AG 2021
Location
Switzerland
ISBN
978-3-030-64609-7
Book
EMBEC 2020, IFMBE Proceedings vol. 80
1680-0737
Periodical
IFMBE PROCEEDINGS
Year of study
80
State
Kingdom of Sweden
Pages from
233
Pages to
239
Pages count
7
URL
https://link.springer.com/chapter/10.1007/978-3-030-64610-3_27
BibTex
@inproceedings{BUT166123, author="Tomáš {Vičar} and Jiří {Chmelík} and Radim {Kolář}", title="Cell Segmentation in Quantitative Phase Images with Improved Iterative Thresholding Method", booktitle="EMBEC 2020, IFMBE Proceedings vol. 80", year="2020", journal="IFMBE PROCEEDINGS", volume="80", pages="233--239", publisher="Springer Nature Switzerland AG 2021", address="Switzerland", doi="10.1007/978-3-030-64610-3\{_}27", isbn="978-3-030-64609-7", issn="1680-0737", url="https://link.springer.com/chapter/10.1007/978-3-030-64610-3_27" }