Automatic ROI positioning in ultrasound TCS images using artificial intelligence to Parkinson´s disease risk
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19240%2F12%3A%230004407" target="_blank" >RIV/47813059:19240/12:#0004407 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Automatic ROI positioning in ultrasound TCS images using artificial intelligence to Parkinson´s disease risk
Original language description
The aim of this work is semi-automatic ROI positioning in transcranial images based on ANN module. We need to learn ANN to accurate positioning of ROI inside substantia nigra of transcranial images. Designed approach is based on image processing and is realized by means of artificial intelligence which has been experimentally simulated in MATLAB software environment. This method is well applicable with Neural Network Toolbox in MATLAB. Within this processing has been worked with a set of TCS images in grayscale and/or binary representation to experimental testing to automatic positioning.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 1st international conference on Biologically Inspired Computation
ISBN
978-1-61804-089-3
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
139-144
Publisher name
WSEAS Press
Place of publication
Faro, Portugalsko
Event location
Faro, Portugalsko
Event date
May 2, 2012
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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