Automated Multi-Contrast Brain Pathological Area Extraction from 2D MR Images

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081731%3A_____%2F15%3A00452295" target="_blank" >RIV/68081731:_____/15:00452295 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/S1665-6423(15)30005-5" target="_blank" >http://dx.doi.org/10.1016/S1665-6423(15)30005-5</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/S1665-6423(15)30005-5" target="_blank" >10.1016/S1665-6423(15)30005-5</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Automated Multi-Contrast Brain Pathological Area Extraction from 2D MR Images

Popis výsledku v původním jazyce

The aim of this work is to propose the fully automated pathological area extraction from multi-parametric 2D MR images of brain. The proposed method is based on multi-resolution symmetry analysis and automatic thresholding. The proposed algorithm first detects the presence of pathology and then starts its extraction. T2 images are used for the presence detection and the multi-contrast MRI is used for the extraction, concretely T2 and FLAIR images. The extraction is based on thresholding, where Otsu's algorithm is used for the automatic determination of the threshold. Since the method is based on symmetry, it works for both axial and coronal planes. In both these planes of healthy brain, the approximate left-right symmetry exists and it is used as the prior knowledge for searching the approximate pathology location. It is assumed that this area is not located symmetrically in both hemispheres, which is met in most cases. The detection algorithm was tested on 203 T2-weighted images and r

Název v anglickém jazyce

Automated Multi-Contrast Brain Pathological Area Extraction from 2D MR Images

Popis výsledku anglicky

The aim of this work is to propose the fully automated pathological area extraction from multi-parametric 2D MR images of brain. The proposed method is based on multi-resolution symmetry analysis and automatic thresholding. The proposed algorithm first detects the presence of pathology and then starts its extraction. T2 images are used for the presence detection and the multi-contrast MRI is used for the extraction, concretely T2 and FLAIR images. The extraction is based on thresholding, where Otsu's algorithm is used for the automatic determination of the threshold. Since the method is based on symmetry, it works for both axial and coronal planes. In both these planes of healthy brain, the approximate left-right symmetry exists and it is used as the prior knowledge for searching the approximate pathology location. It is assumed that this area is not located symmetrically in both hemispheres, which is met in most cases. The detection algorithm was tested on 203 T2-weighted images and r

Druh

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

CEP obor

BH - Optika, masery a lasery

OECD FORD obor

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Projekt

<a href="/cs/project/GAP102%2F12%2F1104" target="_blank" >GAP102/12/1104: Studium metabolizmu a lokalizace primárního mozkového tumoru MR zobrazovacími technikami</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název periodika

Journal of Applied Research and Technology

ISSN

1665-6423

e-ISSN

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Svazek periodika

13

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

MX - Spojené státy mexické

Počet stran výsledku

12

Strana od-do

58-69

Kód UT WoS článku

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EID výsledku v databázi Scopus

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