Edge detection in medical images using the Wavelet Transform

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60461373%3A22340%2F11%3A43892370" target="_blank" >RIV/60461373:22340/11:43892370 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Edge detection in medical images using the Wavelet Transform

Popis výsledku v původním jazyce

Edge detection improves image readability and it is an important part of images preprocessing aimed to their segmentation and automatic recognition of their contents. This paper describes selected methods of edge detection in magnetic resonance images, with the emphasis on the wavelet transform use. Modulus Maxima Method by Stephane Mallat provides the method for edge detection using wavelet transform. This method is based on finding local maxima of horizontal and vertical wavelet coefficients in the first level of wavelet decomposition. It was tested with various wavelet functions both on simulated and real medical images. Presented paper contains a comparison of basic edge detection methods including simple gradient operators and Canny edge detector,and their combination with wavelet transform use. Mathematical principals were studied, as well as application of these methods. All algorithms were developed in the MATLAB environment using Wavelet and Image Processing Toolboxes.

Název v anglickém jazyce

Edge detection in medical images using the Wavelet Transform

Popis výsledku anglicky

Edge detection improves image readability and it is an important part of images preprocessing aimed to their segmentation and automatic recognition of their contents. This paper describes selected methods of edge detection in magnetic resonance images, with the emphasis on the wavelet transform use. Modulus Maxima Method by Stephane Mallat provides the method for edge detection using wavelet transform. This method is based on finding local maxima of horizontal and vertical wavelet coefficients in the first level of wavelet decomposition. It was tested with various wavelet functions both on simulated and real medical images. Presented paper contains a comparison of basic edge detection methods including simple gradient operators and Canny edge detector,and their combination with wavelet transform use. Mathematical principals were studied, as well as application of these methods. All algorithms were developed in the MATLAB environment using Wavelet and Image Processing Toolboxes.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

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)

Rok uplatnění

2011

Kód důvěrnosti údajů

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

Název periodika

Posterus

ISSN

1338-0087

e-ISSN

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Svazek periodika

4

Číslo periodika v rámci svazku

7

Stát vydavatele periodika

SK - Slovenská republika

Počet stran výsledku

8

Strana od-do

1-8

Kód UT WoS článku

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EID výsledku v databázi Scopus

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