Detection of tibial fractures in cats and dogs with deep learning

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dc.authoridUnver, Halil Murat/0000-0001-9959-8425
dc.contributor.authorBaydan, Berker
dc.contributor.authorUnver, Halil Murat
dc.date.accessioned2025-01-21T16:34:18Z
dc.date.available2025-01-21T16:34:18Z
dc.date.issued2021
dc.departmentKırıkkale Üniversitesi
dc.description.abstractThe aim of this study is to classify tibia (fracture/no fracture) on whole/partial body digital images of cats and dogs, and to localize the fracture on fracture tibia by using deep learning methods. This study provides to diagnose fracture on tibia more accurately, quickly and safe for clinicians. In this study, a total of 1488 dog and cat images that were obtained from universities and institutions were used. Three different studies were implemented to detect fracture tibia. In the first phase of the first study, tibia was classified automatically as fracture or no fracture with Mask R-CNN. In the second phase, the fracture location in the fracture tibia image that obtained from the first phase was localized with Mask R-CNN. In the second study, the fracture location was directly localized with Mask R-CNN. In the third study, fracture location in the fracture tibia that obtained from the first phase of first study was localized with SSD. The accuracy and F1 score values in first phase of first study were 74% and 85%, respectively and F1 score value in second phase of first study was 84.5%. The accuracy and F1 score of second study were 52.1% and 68.5%, respectively. The F1 score of third study was 46.2%. The results of the research showed that the first study was promising for detection of fractures in the tibia and the dissemination of the fracture diagnosis with the help of such smart systems would also be beneficial for animal welfare.
dc.identifier.doi10.33988/auvfd.772685
dc.identifier.endpage290
dc.identifier.issn1300-0861
dc.identifier.issn1308-2817
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85108608070
dc.identifier.scopusqualityQ3
dc.identifier.startpage283
dc.identifier.trdizinid442812
dc.identifier.urihttps://doi.org/10.33988/auvfd.772685
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay442812
dc.identifier.urihttps://hdl.handle.net/20.500.12587/23940
dc.identifier.volume68
dc.identifier.wosWOS:000668520700010
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.publisherAnkara Univ Press
dc.relation.ispartofAnkara Universitesi Veteriner Fakultesi Dergisi
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241229
dc.subjectCat; deep learning; dog; fracture; tibia
dc.titleDetection of tibial fractures in cats and dogs with deep learning
dc.title.alternativeDerin öğrenme ile kedi ve köpeklerde tibia kırıklarının tespiti
dc.typeArticle

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