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DC poleHodnotaJazyk
dc.contributor.authorČerný, V.
dc.contributor.authorFekete, L.
dc.contributor.authorZajac, R.
dc.contributor.editorSkala, Václav
dc.date.accessioned2015-09-29T08:49:27Z
dc.date.available2015-09-29T08:49:27Z
dc.date.issued1995
dc.identifier.citationJournal of WSCG. 1995, vol. 3, no. 1-2, p. 357-359.en
dc.identifier.issn1213-6972 (print)
dc.identifier.issn1213-6980 (CD-ROM)
dc.identifier.issn1213-6964 (online)
dc.identifier.urihttp://wscg.zcu.cz/wscg1995/wscg95.htm
dc.identifier.urihttp://hdl.handle.net/11025/16019
dc.format3 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.relation.ispartofseriesJournal of WSCGen
dc.rights© Václav Skala - UNION Agencycs
dc.subjectjednoduchá neuronová síťcs
dc.subjectsonografické lékařské snímkycs
dc.subjectnádorcs
dc.titleTexture classification by neural net in medical sonographyen
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedWe have delevoped a simple neural net classifier to evaluate textural informational content in the sonographic medical images. The net is trained on a set of texture patterns from sonographic images of testes. The samples in the set were classified by the supervisor into two classes: "normal" and "tumor". After the training the performance was 85% correctly classified images. We are in the stage of collecting data for the independent test set of samples.en
dc.subject.translatedsimple neural neten
dc.subject.translatedsonographic medical imagesen
dc.subject.translatedtumoren
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:Volume 3, number 1-2 (1995)

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