Segmentation and Modeling of Scattered RTG Irradiation on Quality of Skiagraphy Images in Clinical Conditions
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F17%3A10238643" target="_blank" >RIV/61989100:27240/17:10238643 - isvavai.cz</a>
Result on the web
<a href="http://ieeexplore.ieee.org/document/8284115/" target="_blank" >http://ieeexplore.ieee.org/document/8284115/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICBDAA.2017.8284115" target="_blank" >10.1109/ICBDAA.2017.8284115</a>
Alternative languages
Result language
angličtina
Original language name
Segmentation and Modeling of Scattered RTG Irradiation on Quality of Skiagraphy Images in Clinical Conditions
Original language description
During the clinical RTG examination, the secondary (scattered) irradiation is produced. This unwanted irradiation is spread into surrounding in the examination room. Unfortunately, is such clinical workspace other skiagraphy images are stored as well. When skiagraphy image is irradiated, its surface and structure may be irreversibly deteriorated. This affect has a severe impact on quality and reproducibility of the clinical information: imagined structures shed contrast and spatial features. Therefore, modelling and estimation of the scattered irradiation is, from clinical point of view, substantially important. Moreover, there are not any methods objectively evaluating a noise level caused by the scattered irradiation. We have used the multiregional segmentation model which is able to extract areas which are affected by the scattered irradiation. On a base of this approach we specify a finite histogram band specifying area of the scattered irradiation. In this regard, we have specified four image features which are used for specification of the irradiation level. In our analysis, we experimentally analysed estimated level of the scattered irradiation in a dependence of a distance skiagraphy image from the RTG device.
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
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Big Data and Analytics (ICBDA) : conference proceedings : November 16-17, 2017, Kuching, Malaysia
ISBN
978-1-5386-0790-9
ISSN
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e-ISSN
neuvedeno
Number of pages
5
Pages from-to
105-110
Publisher name
IEEE
Place of publication
Piscataway
Event location
Kuching
Event date
Nov 16, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000426452100018