COMPARISON OF SEGMENTATION METHODS USED FOR BONE FRACTURE IMAGES

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%.

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Fully automatic segmentation based on localizing active contour method

Proceedings of the 8th International Conference on Ubiquitous Information Management and Communication - ICUIMC '14 ◽

10.1145/2557977.2558036 ◽

2014 ◽

Cited By ~ 2

Author(s):

Toan Bui ◽

Chunsoo Ahn ◽

Yong-woo Lee ◽

Jitae Shin

Keyword(s):

Active Contour ◽

Automatic Segmentation ◽

Contour Method ◽

Active Contour Method ◽

Fully Automatic

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Preliminary process in blast cell morphology identification based on image segmentation methods

International Journal of Electrical and Computer Engineering (IJECE) ◽

10.11591/ijece.v10i6.pp5714-5725 ◽

2020 ◽

Vol 10 (6) ◽

pp. 5714

Author(s):

Retno Supriyanti ◽

Pangestu F. Wibowo ◽

Fibra R. Firmanda ◽

Yogi Ramadhani ◽

Wahyu Siswandari

Keyword(s):

Active Contour ◽

Complete Blood Count ◽

Blast Cell ◽

Contour Method ◽

Blood Disorders ◽

Active Contour Method ◽

Segmentation Methods ◽

Watershed Method ◽

Further Development ◽

Error Percentage

The diagnosis of blood disorders in developing countries usually uses the diagnostic procedure Complete Blood Count (CBC). This is due to the limitations of existing health facilities so that examinations use standard microscopes as required in CBC examinations. However, the CBC process still poses a problem, namely that the procedure for manually counting blood cells with a microscope requires a lot of energy and time, and is expensive. This paper will discuss alternative uses of image processing technology in blast cell identification by using microscope images. In this paper, we will discuss in detail the morphological measurements which include the diameter, circumference and area of blast cell cells based on watershed segmentation methods and active contour. As a basis for further development, we compare the performance between the uses of both methods. The results show that the active contour method has an error percentage of 5.15% while the watershed method has an error percentage of 8.25%.

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