Path Descriptors for Geometric Graph Matching and Registration
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F14%3A00223693" target="_blank" >RIV/68407700:21230/14:00223693 - isvavai.cz</a>
Result on the web
<a href="http://cmp.felk.cvut.cz/pub/cmp/articles/amavemig/Pinheiro-ICIAR2014.pdf" target="_blank" >http://cmp.felk.cvut.cz/pub/cmp/articles/amavemig/Pinheiro-ICIAR2014.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-11758-4_1" target="_blank" >10.1007/978-3-319-11758-4_1</a>
Alternative languages
Result language
angličtina
Original language name
Path Descriptors for Geometric Graph Matching and Registration
Original language description
Graph and tree-like structures such as blood vessels and neuronal networks are abundant in medical imaging. We present a method to calculate path descriptors in geometrical graphs, so that the similarity between paths in the graphs can be determined efficiently. We show experimentally that our descriptors are more discriminative than existing alternatives. We further describe how to match two geometric graphs using our path descriptors. Our main application is registering images for which standard techniques are inefficient, because the appearance of the images is too different, or there is not enough texture and no uniquely identifiable keypoints to be found. We show that our approach can register these images with better accuracy than previous methods.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
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
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Image Analysis and Recognition: 11th International Conference (ICIAR 2014)
ISBN
978-3-319-11757-7
ISSN
0302-9743
e-ISSN
—
Number of pages
9
Pages from-to
3-11
Publisher name
Springer-Verlag
Place of publication
Berlin
Event location
Vilamoura, Algarve
Event date
Oct 22, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000345583300001