KONDRATĚV, Alexandr and Dmitry SOROKIN. Automatic detection of laser-induced structures in live cell fluorescent microscopy images using snakes with geometric constraints. In 23rd International Conference on Pattern Recognition, ICPR 2016. Cancun, Mexico: Institute of Electrical and Electronics Engineers Inc., 2017, p. 331-336. ISBN 978-1-5090-4847-2. Available from: https://dx.doi.org/10.1109/ICPR.2016.7899655.
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Basic information
Original name Automatic detection of laser-induced structures in live cell fluorescent microscopy images using snakes with geometric constraints
Authors KONDRATĚV, Alexandr (643 Russian Federation) and Dmitry SOROKIN (643 Russian Federation, belonging to the institution).
Edition Cancun, Mexico, 23rd International Conference on Pattern Recognition, ICPR 2016, p. 331-336, 6 pp. 2017.
Publisher Institute of Electrical and Electronics Engineers Inc.
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Switzerland
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
RIV identification code RIV/00216224:14330/17:00100647
Organization unit Faculty of Informatics
ISBN 978-1-5090-4847-2
ISSN 1051-4651
Doi http://dx.doi.org/10.1109/ICPR.2016.7899655
UT WoS 000406771300058
Keywords in English Argon lasers; Cells; Cytology; Fluorescence; Geometry; Image registration; Image segmentation; Matrix algebra
Tags firank_A
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 5/11/2021 15:36.
Abstract
The existence of reliable evaluation datasets for cell image registration algorithms is crucial for quantitative comparison of registration approaches. A new technique for creating real live cell image sequences for this purpose was introduced recently. These datasets contain stable structures bleached by argon laser in the cell nucleus. In this work, we propose an approach for automatic detection of laser-induced linear structures in live cell fluorescent microscopy images. Compared to a previous linear laser-induced structure detection approach, our method employs an active contours model with a Hessian-based image energy term for linear structures enhancement and geometric energy term controlling the geometric relations between the structures. It uses position adaptive tension parameter values to adjust the snakes behavior in problematic regions (end points and intersection points) and a temporal consistent scheme where the results from the previous frame are used as an initial approximation for the current frame. Our approach was successfully applied to real live cell microscopy image sequences and an experimental comparison with an existing laser-induced structures detection method based on minimal paths has been performed.
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