A reproducible method to transcranial B-MODE ultrasound images analysis based on echogenicity evaluation in selectable ROI

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19240%2F14%3A%230005334" target="_blank" >RIV/47813059:19240/14:#0005334 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/47813059:19240/14:#0005345

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

A reproducible method to transcranial B-MODE ultrasound images analysis based on echogenicity evaluation in selectable ROI

Popis výsledku v původním jazyce

The presented paper demonstrates how to detect pathological issues in transcranial B-MODE ultrasound images. We developed an algorithm based on binary thresholding with subsequential computing of area inside ROI which represents an area in which we detect the issue. We work with a collection of images acquisted from 3 different ultrasound machines. We detect echogenic area in substantia nigra which is primary feature to Morbus Parkinson and also raphe nucleus echogenicity to detection of other neurological diseases. All achieved results were verified by an erudite neuroso nologist and based on statistics such as correlation and kappa analysis. Average correlation between observers r > 0.88, level of agreement kappa > 0.82. So, we proved that developedalgorithm is highly reproducible and also could be used for different cases, not only in neurology due to principle of B-MODE imaging.The algorithm has been implemented in MATLAB with Image Processing Toolbox.Achieved results will verifie

Název v anglickém jazyce

A reproducible method to transcranial B-MODE ultrasound images analysis based on echogenicity evaluation in selectable ROI

Popis výsledku anglicky

The presented paper demonstrates how to detect pathological issues in transcranial B-MODE ultrasound images. We developed an algorithm based on binary thresholding with subsequential computing of area inside ROI which represents an area in which we detect the issue. We work with a collection of images acquisted from 3 different ultrasound machines. We detect echogenic area in substantia nigra which is primary feature to Morbus Parkinson and also raphe nucleus echogenicity to detection of other neurological diseases. All achieved results were verified by an erudite neuroso nologist and based on statistics such as correlation and kappa analysis. Average correlation between observers r > 0.88, level of agreement kappa > 0.82. So, we proved that developedalgorithm is highly reproducible and also could be used for different cases, not only in neurology due to principle of B-MODE imaging.The algorithm has been implemented in MATLAB with Image Processing Toolbox.Achieved results will verifie

Druh

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

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: Centrum excelence IT4Innovations</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název periodika

INTERNATIONAL JOURNAL OF BIOLOGY AND BIOMEDICAL ENGINEERING

ISSN

1998-4510

e-ISSN

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Svazek periodika

8/2014

Číslo periodika v rámci svazku

8

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

9

Strana od-do

98-106

Kód UT WoS článku

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EID výsledku v databázi Scopus

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