Fuzzy C-Means Based Liver CT Image Segmentation with Optimum Number of Clusters

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86092552" target="_blank" >RIV/61989100:27240/14:86092552 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/14:86092552
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-08156-4_14" target="_blank" >http://dx.doi.org/10.1007/978-3-319-08156-4_14</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-08156-4_14" target="_blank" >10.1007/978-3-319-08156-4_14</a>

Result language
angličtina
Original language name
Fuzzy C-Means Based Liver CT Image Segmentation with Optimum Number of Clusters
Original language description
In this paper, we investigate the effect of using an optimum number of clusters with Fuzzy C-Means clustering, for Liver CT image segmentation. The optimum number of clusters to be used was measured using the average silhouette value. The evaluation was carried out using the Jaccard index, in which we concluded that using the optimum number of clusters may not necessarily lead to the best segmentation results. Springer International Publishing Switzerland 2014.
Czech name
—
Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Advances in Intelligent Systems and Computing. Volume 303
ISBN
978-3-319-08155-7
ISSN
2194-5357
e-ISSN
—
Number of pages
9
Pages from-to
131-139
Publisher name
Springer-Verlag Berlin Heidelberg
Place of publication
Berlin Heidelberg
Event location
Ostrava
Event date
Jun 23, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000342841800014

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