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001-es BibID:	BIBFORM104443
035-os BibID:	(Pubmed)36083935 (cikkazonosító)22030394 (Scopus)85138127061
Első szerző:	Kupás Dávid (programtervező informatikus)
Cím:	Classification of Pap-smear cell images using deep convolutional neural network accelerated by hand-crafted features / Dávid Kupás, Balázs Harangi
Dátum:	2022
Megjegyzések:	The classification of cells extracted from Papsmears is in most cases done using neural network architectures. Nevertheless, the importance of features extracted with digital image processing is also discussed in many related articles. Decision support systems and automated analysis tools of Papsmears often use these kinds of manually extracted, global features based on clinical expert opinion. In this paper, a solution is introduced where 29 different contextual features are combined with local features learned by a neural network so that it increases classification performance. The weight distribution between the features is also investigated leading to a conclusion that the numerical features are indeed forming an important part of the learning process. Furthermore, extensive testing of the presented methods is done using a dataset annotated by clinical experts. An increase of 3.2% in F1-Score value can be observed when using the combination of contextual and local features.
Tárgyszavak:	Műszaki tudományok Informatikai tudományok előadáskivonat könyvrészlet
Megjelenés:	1-4.
További szerzők:	Harangi Balázs (1986-) (programtervező matematikus)
Pályázati támogatás:	GINOP-2.2.1- 18-2018-00012 GINOP
Internet cím:	Intézményi repozitóriumban (DEA) tárolt változat DOI
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