Active partition based medical image understanding with self-organised competitive spatch eduction

dc.contributor.author	Pryczek, Michał
dc.contributor.author	Tomczyk, Arkadiusz
dc.contributor.author	Szczepaniak, Piotr
dc.date.accessioned	2015-06-03T11:15:59Z
dc.date.available	2015-06-03T11:15:59Z
dc.date.issued	2010
dc.description.abstract	Medical Image Understanding is a recently defined semantic oriented image recognition task. Its specific requirements, highlighting complex characteristics of recognised objects as well as indispensable use of human-level expert knowledge almost every step of data processing sets new requirements for implemented algorithms. This paper focuses on linguistic image description method, designed to segment low level, semantically coherent image regions and mine adjacency relations among them. Example method results on medical images are presented to specify some methods properties.	en_EN
dc.format	application/pdf
dc.identifier.citation	Journal of Applied Computer Science., 2010 Vol.18 nr 2 s.67-78 sum.
dc.identifier.issn	1507-0360
dc.identifier.other	0000027590
dc.identifier.uri	http://hdl.handle.net/11652/448
dc.language.iso	en
dc.publisher	Wydawnictwo Politechniki Łódzkiej	pl_PL
dc.publisher	Lodz University of Technology. Press	en_EN
dc.relation.ispartofseries	Journal of Applied Computer Science., 2010 Vol.18 nr 2	en_EN
dc.title	Active partition based medical image understanding with self-organised competitive spatch eduction
dc.type	Artykuł

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