Detection of tibial fractures in cats and dogs with deep learning
Yıl: 2021 Cilt: 68 Sayı: 3 Sayfa Aralığı: 283 - 290 Metin Dili: İngilizce DOI: 10.33988/auvfd.772685 İndeks Tarihi: 29-07-2022
Detection of tibial fractures in cats and dogs with deep learning
Öz: The 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 moreaccurately, quickly and safe for clinicians. In this study, a total of 1488 dog and cat images that were obtained from universities andinstitutions were used. Three different studies were implemented to detect fracture tibia. In the first phase of the first study, tibia wasclassified automatically as fracture or no fracture with Mask R-CNN. In the second phase, the fracture location in the fracture tibiaimage that obtained from the first phase was localized with Mask R-CNN. In the second study, the fracture location was directlylocalized with Mask R-CNN. In the third study, fracture location in the fracture tibia that obtained from the first phase of first studywas localized with SSD. The accuracy and F1 score values in first phase of first study were 74% and 85%, respectively and F1 scorevalue in second phase of first study was 84.5%. The accuracy and F1 score of second study were 52.1% and 68.5%, respectively. TheF1 score of third study was 46.2%. The results of the research showed that the first study was promising for detection of fractures inthe tibia and the dissemination of the fracture diagnosis with the help of such smart systems would also be beneficial for animal welfare.
Anahtar Kelime: Derin öğrenme ile kedi ve köpeklerde tibia kırıklarının tespiti
Öz: Bu çalışmanın amacı derin öğrenme yöntemleri kullanarak kedilerin ve köpeklerin bütün/kısmi dijital görüntüleri üzerinde tibiayı (kırık/kırık değil) sınıflandırmak ve kırık olarak tespit edilmiş tibialar üzerinde kırığın yerini lokalize etmektir. Bu çalışma klinisyenler için tibiadaki kırığın daha doğru, hızlı ve güvenli bir şekilde teşhis edilmesini sağlar. Bu araştırmada üniversitelerden ve kurumlardan sağlanan toplam 1488 adet köpek ve kedi görüntüsü kullanıldı. Tibia kırığı tespiti için üç farklı çalışma yapıldı. İlk çalışmanın ilk fazında, Mask R-CNN ile otomatik şekilde kırık ve sağlam tibia sınıflandırılması yapıldı. İkinci fazda ilk fazdan elde edilen kırık tibiadaki kırık yeri Mask R-CNN ile lokalize edildi. İkinci çalışmada, Mask R-CNN ile kırığın yeri doğrudan lokalize edildi. Üçüncü çalışmada SSD ile birinci çalışmanın birinci fazından elde edilen kırık tibiadaki kırık yeri lokalize edildi. İlk çalışmanın ilk faz doğruluk ve F1 skor değerleri sırasıyla %74 ve %85, birinci çalışmanın ikinci faz F1 skor değeri ise %84,5 olarak bulundu. İkinci çalışmanın doğruluk ve F1 skor değerleri sırasıyla %52,1 ve %68,5 olarak bulundu. Üçüncü çalışmanın F1 skor değeri ise %46,2 olarak bulundu. Araştırma sonuçları, ilk çalışmanın tibiada kırık tespiti için umut verici olduğunu ve bu tip akıllı sistemler yardımıyla kırık teşhisinin yaygınlaştırılmasının hayvan refahı yönünden de yararlı olacağını gösterdi.
Anahtar Kelime: Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
- 1. Bennour EM, Abushhiwa MA, Ben Ali L, et al (2014): A retrospective study on appendicular fractures in dogs and cats in Tripoli – Libya. J Vet Adv, 4, 425-431.
- 2. Chung SW, Han SS, Lee JW, et al (2018): Automated detection and classification of the proximal humerus fracture by using deep learning algorithm. Acta Orthop, 89, 468-473.
- 3. Eksi Z, Dandil E, Cakiroglu M (2012): Computer aided bone fracture detection. In: 2012 20th Signal Processing and Communications Applications Conference (SIU). Muğla, Turkey.
- 4. Glyde M, Arnett R (2006): Tibial fractures in the dog and cat: options for management. Ir Vet J, 59, 290-295.
- 5. Hayashi K, Kapatkin AS (2012): Fractures of the tibia and fibula, 999-1014. In: KM Tobias, SA Johnston (Eds), Veterinary Surgery Small Animal. Volume One, E-BOOK: 2-Volume Set, Elsevier Inc., Canada.
- 6. He K, Hkioxari G, Dollar P et al (2018): Mask R-CNN. 2980-2988. In: IEEE International Conference on Computer Vision (ICCV). Venice, Italy. arXiv:1703.06870v3 [cs.CV].
- 7. Joshi D, Singh T (2020): A survey of fracture detection techniques in bone x-ray images. Artif Intell Rev, 53, 4475– 4517.
- 8. Kalmet PHS, Sanduleanu S, Primakov S et al (2020): Deep learning in fracture detection: a narrative review. Acta Orthop, 91, 215-220.
- 9. Khan M, Sirdeshmukh, SPSMA, Javed K (2016): Evaluation of Bone Fracture in Animal Model Using Bio‐ electrical Impedance Analysis. Perspectives in Science, 8, 567-569.
- 10. Khatik I (2017): A study of various bone fracture detection techniques. Int J Eng Comput Sci, 6, 21418-21423.
- 11. Kim DH, MacKinnon T (2017): Artificial intelligence in fracture detection: transfer learning from deep convolutional neural networks. Clin Radiol, 73, 439-445.
- 12. Liu W, Anguelov D, Erhan D et al (2016): SSD: Single Shot MultiBox Detector. arXiv:1512.02325 [cs.CV]. Available at https://arxiv.org/pdf/1512.02325.pdf. (Accessed October 21, 2020).
- 13. Mahendran SK, Santhosh Baboo S (2011): An enhanced tibia fracture detection tool using image processing and classification fusion techniques in x-ray images. GJCST, 11, 23-28.
- 14. Olczak J, Fahlberg N, Maki A et al (2017). Artificial intelligence for analysing orthopaedic trauma radiographs. Acta Orthop, 88, 581-586.
- 15. Rani S, Kumari M, Amulya G et al (2019): Leg bone fracture segmentation and detection using advanced morphplogical techniques. Int J Recent Technol Eng, 8, 1246-1249.
- 16. Ravi D, Wong C, Deligianni F et al (2017): Deep Learning for Health Informatics. IEEE J Biomed Health, 21, 4-21.
- 17. Tsuruoka Y, Tsujii J (2003): Boosting precision and recall of dictionary-based protein name recognition. 41-48. In: Proceedings of the ACL 2003 workshop on Natural language processing in biomedicine. Sapporo, Japan.
- 18. Tychsen-Smith L, Petersson L (2018): Improving object localization with fitness nms and bounded IOU loss. arXiv:1711.00164v3 [cs.CV]. Available at https://arxiv.org/pdf/1711.00164.pdf. (Accessed July 21, 2020).
- 19. Tzutalin (2015): LabelImg. Git code. Available at https://github.com/tzutalin/labelImg. (Accessed February 27, 2020).
| APA | Baydan B, Unver H (2021). Detection of tibial fractures in cats and dogs with deep learning. , 283 - 290. 10.33988/auvfd.772685 |
| Chicago | Baydan Berker,Unver Halil Murat Detection of tibial fractures in cats and dogs with deep learning. (2021): 283 - 290. 10.33988/auvfd.772685 |
| MLA | Baydan Berker,Unver Halil Murat Detection of tibial fractures in cats and dogs with deep learning. , 2021, ss.283 - 290. 10.33988/auvfd.772685 |
| AMA | Baydan B,Unver H Detection of tibial fractures in cats and dogs with deep learning. . 2021; 283 - 290. 10.33988/auvfd.772685 |
| Vancouver | Baydan B,Unver H Detection of tibial fractures in cats and dogs with deep learning. . 2021; 283 - 290. 10.33988/auvfd.772685 |
| IEEE | Baydan B,Unver H "Detection of tibial fractures in cats and dogs with deep learning." , ss.283 - 290, 2021. 10.33988/auvfd.772685 |
| ISNAD | Baydan, Berker - Unver, Halil Murat. "Detection of tibial fractures in cats and dogs with deep learning". (2021), 283-290. https://doi.org/10.33988/auvfd.772685 |
| APA | Baydan B, Unver H (2021). Detection of tibial fractures in cats and dogs with deep learning. Ankara Üniversitesi Veteriner Fakültesi Dergisi, 68(3), 283 - 290. 10.33988/auvfd.772685 |
| Chicago | Baydan Berker,Unver Halil Murat Detection of tibial fractures in cats and dogs with deep learning. Ankara Üniversitesi Veteriner Fakültesi Dergisi 68, no.3 (2021): 283 - 290. 10.33988/auvfd.772685 |
| MLA | Baydan Berker,Unver Halil Murat Detection of tibial fractures in cats and dogs with deep learning. Ankara Üniversitesi Veteriner Fakültesi Dergisi, vol.68, no.3, 2021, ss.283 - 290. 10.33988/auvfd.772685 |
| AMA | Baydan B,Unver H Detection of tibial fractures in cats and dogs with deep learning. Ankara Üniversitesi Veteriner Fakültesi Dergisi. 2021; 68(3): 283 - 290. 10.33988/auvfd.772685 |
| Vancouver | Baydan B,Unver H Detection of tibial fractures in cats and dogs with deep learning. Ankara Üniversitesi Veteriner Fakültesi Dergisi. 2021; 68(3): 283 - 290. 10.33988/auvfd.772685 |
| IEEE | Baydan B,Unver H "Detection of tibial fractures in cats and dogs with deep learning." Ankara Üniversitesi Veteriner Fakültesi Dergisi, 68, ss.283 - 290, 2021. 10.33988/auvfd.772685 |
| ISNAD | Baydan, Berker - Unver, Halil Murat. "Detection of tibial fractures in cats and dogs with deep learning". Ankara Üniversitesi Veteriner Fakültesi Dergisi 68/3 (2021), 283-290. https://doi.org/10.33988/auvfd.772685 |
