Detection of foot bone anomaly using medical photogrammetry

Authors : Hatice ÇATAL REİS

Pages : 1-5

Doi:10.26833/ijeg.333686

View : 9 | Download : 6

Publication Date : 2018-02-01

Article Type : Research Paper

Abstract :Photogrammetry has been used for medical diagnostic and treatment. Mostly used medical photogrammetric techniques are Ultrasound, Computed Tomography insert ignore into journalissuearticles values(CT); and Magnetic Resonance Imaging insert ignore into journalissuearticles values(MRI); images. CT and MRI are the most effective method for the early detection of foot and ankle anomaly. Researchers have been developing various methods to detect anomaly. Many image segmentation techniques are available in the literature. Computer Aided Diagnosing insert ignore into journalissuearticles values(CAD); system has been proposed in this study for detection of foot bone anomaly by the analysis of CT images. In this study, a segmentation based on edge detection method is proposed for the classification of anomaly in foot CT images. Edge detection algorithms are the most commonly used techniques in image processing for edge detection. Canny edge detector is evaluated in this study. In this study, “.dicom” medical image standard format and ten male patient`s foot CT images insert ignore into journalissuearticles values(245 images and 50 test data); are used. The used parameters are detector collimation of 64 mm, scanning thickness of 1-5 mm, and pixel sizes of 512x512 in radiometric resolution of 16 bits’ gray levels. The proposed method consists of five major steps: insert ignore into journalissuearticles values(i); calculating the horizontal & vertical gradient, insert ignore into journalissuearticles values(ii); determining gradient magnitude and gradient direction, insert ignore into journalissuearticles values(iii); applying non-maximal suppression, insert ignore into journalissuearticles values(iv); computing high and low thresholds, insert ignore into journalissuearticles values(v); hysteresis thresholding are applied to the multi-detector computed tomography to detect the bone anomaly. In this study, automatic edge-based digital image processing techniques are applied to detect of foot bone anomaly. The proposed canny segmentation method enables users segment anomaly in MDCT of foot very quickly and efficiently. The results demonstrate that the proposed segmentation method is effective for segmenting anomaly. The proposed method obtains satisfactory performances in terms of accuracy and F-measure the area under Receiver Operating Characteristic curve insert ignore into journalissuearticles values(ROC curve insert ignore into journalissuearticles values(AUC););. The proposed segmentation method achieves an accuracy of 0.86 and F- measure of 0.92, respectively. The purpose of our study is to detect the anomaly of the foot and it was the simplest and less time consuming process.
Keywords : Medical Photogrammetry, Medical Image Processing, Segmentation, Anomaly, CT