Comparison of segmentation methods used for bone fracture images

Küçük Resim Yok

Tarih

2021

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

Künye