Surface of articular cartilage extraction using fuzzy C-means segmentation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F16%3A86099577" target="_blank" >RIV/61989100:27240/16:86099577 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-319-31277-4_18" target="_blank" >http://dx.doi.org/10.1007/978-3-319-31277-4_18</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-31277-4_18" target="_blank" >10.1007/978-3-319-31277-4_18</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Surface of articular cartilage extraction using fuzzy C-means segmentation

Popis výsledku v původním jazyce

The article deals with complex segmentation approach which is focused on detection of pathological changes on the articular cartilage surface. There is a significant problem, in the clinical practice with recognition of individual structures of cartilage surface. Cartilages are normally investigated either by ultrasound or MRI. Both methods give output images in shade level spectrum. This fact is severe problem for detection especially small changes which indicate surface deterioration. This pathological stage often leads to further development of disease which cause to total loss of articular cartilage. The proposed software approach partially solves mentioned problem. The core of segmentation is based on fuzzy C-means algorithm which is very sensitive even in the noisy environment and for tiny structures as well. Furthermore, color transformation is implemented. This key benefit of proposed software allows transformation physiological cartilage to color spectrum, other tissues are suppressed. In the output, we give mathematical model of articular cartilage with detection of pathological discontinuities.

Název v anglickém jazyce

Surface of articular cartilage extraction using fuzzy C-means segmentation

Popis výsledku anglicky

The article deals with complex segmentation approach which is focused on detection of pathological changes on the articular cartilage surface. There is a significant problem, in the clinical practice with recognition of individual structures of cartilage surface. Cartilages are normally investigated either by ultrasound or MRI. Both methods give output images in shade level spectrum. This fact is severe problem for detection especially small changes which indicate surface deterioration. This pathological stage often leads to further development of disease which cause to total loss of articular cartilage. The proposed software approach partially solves mentioned problem. The core of segmentation is based on fuzzy C-means algorithm which is very sensitive even in the noisy environment and for tiny structures as well. Furthermore, color transformation is implemented. This key benefit of proposed software allows transformation physiological cartilage to color spectrum, other tissues are suppressed. In the output, we give mathematical model of articular cartilage with detection of pathological discontinuities.

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

—

Projekt

<a href="/cs/project/TG01010137" target="_blank" >TG01010137: PRE SEED fond VŠB-Technické univerzity Ostrava</a><br>

Návaznosti

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

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

Studies in Computational Intelligence. Volume 642

ISBN

978-3-319-31276-7

ISSN

1860-949X

e-ISSN

—

Počet stran výsledku

11

Strana od-do

209-219

Název nakladatele

Springer Verlag

Místo vydání

London

Místo konání akce

Danang

Datum konání akce

14. 3. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000390824900018