Abstract
Abstract. 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 Karabük 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%.
Highlights
Imaging processes and software applications, which are an effective way for diagnosis and treatment in the biomedical field, are becoming increasingly popular
While applications in biomedical field carry out these processes, the necessary images are obtained from biomedical imaging devices
The aim of this study is to compare the segmentation methods used in studies on bone fracture images, find the most successful one and why the preferred method should be applied on the bone fracture images
Summary
Imaging processes and software applications, which are an effective way for diagnosis and treatment in the biomedical field, are becoming increasingly popular. These two fields provide great convenience to doctors, clinicians, scientists and medical device users. Software applications that can automatically analyze are helpful tools used to extract information about subjects like disease diagnosis, organ damage, experimental studies and fracture detection, etc. One of the projects carried out in the biomedical field in recent years is to detect bone fractures in any part of the body and inform physicians and radiologists about them. While applications in biomedical field carry out these processes, the necessary images are obtained from biomedical imaging devices. The quality of images is very crucial for the high accuracy of features to be detected or information to be extracted
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