Automatic detection of laser-induced structures in live cell fluorescent microscopy images using snakes with geometric constraints
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F17%3A00100647" target="_blank" >RIV/00216224:14330/17:00100647 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/ICPR.2016.7899655" target="_blank" >http://dx.doi.org/10.1109/ICPR.2016.7899655</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICPR.2016.7899655" target="_blank" >10.1109/ICPR.2016.7899655</a>
Alternative languages
Result language
angličtina
Original language name
Automatic detection of laser-induced structures in live cell fluorescent microscopy images using snakes with geometric constraints
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
23rd International Conference on Pattern Recognition, ICPR 2016
ISBN
9781509048472
ISSN
1051-4651
e-ISSN
—
Number of pages
6
Pages from-to
331-336
Publisher name
Institute of Electrical and Electronics Engineers Inc.
Place of publication
Cancun, Mexico
Event location
Cancun, Mexico
Event date
Jan 1, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000406771300058