A Quantitative and Comparative Analysis of Edge Detectors for Biomedical Image Identification Within Dynamical Noise Effect
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F20%3A10244964" target="_blank" >RIV/61989100:27240/20:10244964 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-030-42058-1_8" target="_blank" >http://dx.doi.org/10.1007/978-3-030-42058-1_8</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-42058-1_8" target="_blank" >10.1007/978-3-030-42058-1_8</a>
Alternative languages
Result language
angličtina
Original language name
A Quantitative and Comparative Analysis of Edge Detectors for Biomedical Image Identification Within Dynamical Noise Effect
Original language description
Image processing plays a key role in many medical imaging applications, by automation and making delineation of regions of interest more simple. The paper describes image processing such as image properties, noise generators and edge detectors. The work deals with methods of edge detection in biomedical images using real data sets. The aim of this work are experiments providing information about the detector noise resistance. Another aim is own implementation of selected edge detection operators and an application on different types of data created by magnetic resonance imaging and computed tomography. Theoretical and experimental comparisons of edge detectors are presented. (C) 2020, Springer Nature Switzerland AG.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10200 - Computer and information sciences
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Volume 12034
ISBN
978-3-030-42057-4
ISSN
0302-9743
e-ISSN
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Number of pages
12
Pages from-to
90-101
Publisher name
Springer
Place of publication
Cham
Event location
Phuket
Event date
Mar 23, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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