Comparison of segmentation methods used for bone fracture images
Küçük Resim Yok
Tarih
2021
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
International Society for Photogrammetry and Remote Sensing
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
The usage of computers and software in the biomedical field has been increasing and applications for doctors, clinicians, scientists and other users have been developed in the recent times. Manual, semi-Automatic and fully automatic applications developed for bone fracture detection are one of the important studies in this field. Image segmentation, which is one of the image preprocessing steps in bone fracture detection, is an important step to obtain successful results with high accuracy. In this study, Otsu thresholding method, active contour method, k-means method, fuzzy c-mean method, Niblack thresholding method and max min thresholding range (MMTR) method are used on bone images obtained by Karabuk University Training and Research Hospital. When any filters are not applied on images to remove noises, the most successful method is obtained by K-means method based on specificity and accuracy as 89,55% and 83,31% respectively. Niblack thresholding method has the highest sensitivity result as 92,45%. © Author(s) 2021. CC BY 4.0 License.
Açıklama
6th International Conference on Smart City Applications -- 27 October 2021 through 29 October 2021 -- Safranbolu -- 175815
Anahtar Kelimeler
Bone Fracture, Fracture Diagnosis, Image Processing, Segmentation Methods, Thresholding
Kaynak
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
46
Sayı
4/W5-2021
