Edge Detection in Biomedical Images Using Self-Organizing Maps
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F13%3A43894972" target="_blank" >RIV/60461373:22340/13:43894972 - isvavai.cz</a>
Result on the web
<a href="http://www.intechopen.com/books/artificial-neural-networks-architectures-and-applications/edge-detection-in-biomedical-images-using-self-organizing-maps" target="_blank" >http://www.intechopen.com/books/artificial-neural-networks-architectures-and-applications/edge-detection-in-biomedical-images-using-self-organizing-maps</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5772/51468" target="_blank" >10.5772/51468</a>
Alternative languages
Result language
angličtina
Original language name
Edge Detection in Biomedical Images Using Self-Organizing Maps
Original language description
The application of self-organizing maps (SOMs) to the edge detection in biomedical images is discussed. The SOM algorithm has been implemented in MATLAB program suite with various optional parameters enabling the adjustment of the model according to theuser?s requirements. For easier application of SOM the graphical user interface has been developed. The edge detection procedure is a critical step in the analysis of biomedical images, enabling for instance the detection of the abnormal structure or therecognition of different types of tissue. The self-organizing map provides a quick and easy approach for edge detection tasks with satisfying quality of outputs, which has been verified using the high-resolution computed tomography images capturing theexpressions of the Granulomatosis with polyangiitis. The obtained results have been discussed with an expert as well.
Czech name
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Czech description
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Classification
Type
C - Chapter in a specialist book
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
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Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Book/collection name
Artificial Neural Networks - Architectures and Applications
ISBN
978-953-51-0935-8
Number of pages of the result
19
Pages from-to
125-143
Number of pages of the book
256
Publisher name
InTech
Place of publication
Rijeka
UT code for WoS chapter
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