Edge Detection in Biomedical Images Using Self-Organizing Maps

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Edge Detection in Biomedical Images Using Self-Organizing Maps

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Edge Detection in Biomedical Images Using Self-Organizing Maps

Popis výsledku anglicky

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.

Druh

C - Kapitola v odborné knize

CEP obor

JD - Využití počítačů, robotika a její aplikace

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2013

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název knihy nebo sborníku

Artificial Neural Networks - Architectures and Applications

ISBN

978-953-51-0935-8

Počet stran výsledku

19

Strana od-do

125-143

Počet stran knihy

256

Název nakladatele

InTech

Místo vydání

Rijeka

Kód UT WoS kapitoly

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