Отрывок: Although in the case of a successful boundary detection result, there is no need to adjust the boundary, such a frag- ment of the algorithm reduces the number of further calcula- tions when searching for the required reference characteris- tics, which ultimately leads to program acceleration. Fig. 4. Boundary detection by proposed algorithm Experiments The experiments were carried out on 20 images of...
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dc.contributor.authorAl-Temimi, A.M.S.-
dc.contributor.authorPilidi, V.S.-
dc.contributor.authorIbraheem, M.K.I.-
dc.date.accessioned2023-05-04 11:00:52-
dc.date.available2023-05-04 11:00:52-
dc.date.issued2022-06-
dc.identifierDspace\SGAU\20230413\103046ru
dc.identifierDspace\SGAU\20230426\103046ru
dc.identifierDspace\SGAU\20230503\103046ru
dc.identifier.citationAl-Temimi AMS, Pilidi VS, Ibraheem MKI. Novel approach of simplification detected contours on X-ray medical images. Computer Optics 2022; 46(3): 479-482. DOI: 10.18287/2412-6179-CO-1014.ru
dc.identifier.urihttps://dx.doi.org/10.18287/2412-6179-CO-1014-
dc.identifier.urihttp://repo.ssau.ru/handle/Zhurnal-Komputernaya-optika/Novel-approach-of-simplification-detected-contours-on-Xray-medical-images-103046-
dc.description.abstractThis paper gives description of a method for simplifying the number of points representing detected contours of the bones on digital X-ray images. Such simplification permits simplify way for correction the location of these points in the cases, if the analyzed image has poor quality, and to reduces the time of analysis it to get the reference lines and angles for diagnosis purposes of the area under investigation.ru
dc.language.isoenru
dc.publisherСамарский национальный исследовательский университетru
dc.relation.ispartofseries46;3-
dc.subjectobject recognitionru
dc.subjectdigital X-ray imageru
dc.subjectreference lines and anglesru
dc.subjectcontour simplificationru
dc.subjectmedicine diagnosis systemru
dc.titleNovel approach of simplification detected contours on X-ray medical imagesru
dc.typeArticleru
dc.textpartAlthough in the case of a successful boundary detection result, there is no need to adjust the boundary, such a frag- ment of the algorithm reduces the number of further calcula- tions when searching for the required reference characteris- tics, which ultimately leads to program acceleration. Fig. 4. Boundary detection by proposed algorithm Experiments The experiments were carried out on 20 images of...-
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