Fully automatic segmentation of stained histological cuts

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F13%3A00211381" target="_blank" >RIV/68407700:21230/13:00211381 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Fully automatic segmentation of stained histological cuts
Original language description
The paper describes an automatic unsupervised segmentation of stained histological sections, which would be suitable for further registration of series of stained consecutive histological cuts. We combine some already existing methods - Gaussian Mixturemodel above colour histogram, superpixels to increase the robustness and speed and the Graph Cut method to obtain compact segmentation. We show the experimental results and segmentation precision on both synthetic and real histological images. For synthetic images we reach mean classification error for 4-class segmentation of about 3%. The unsupervised segmentation on real images shows us always reasonable object, which is important for future segmentation-based registration.
Czech name
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Czech description
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Project
<a href="/en/project/GAP202%2F11%2F0111" target="_blank" >GAP202/11/0111: Automatic analysis of light and electron microscopy neuronal data</a><br>
Continuities
S - Specificky vyzkum na vysokych skolach

Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
POSTER 2013 - 17th International Student Conference on Electrical Engineering
ISBN
978-80-01-05242-6
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
1-7
Publisher name
Czech Technical University
Place of publication
Prague
Event location
Prague
Event date
May 16, 2013
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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