Photogrammetry has been used for medicaldiagnostic and treatment. Generally, medical photogrammetric techniques areused Ultrasound, Computed Tomography (CT) and Magnetic Resonance Imaging (MRI)images. CT and MRI are the mosteffective method for the early detection of foot and ankle anomaly. Researchershave been developing various methods to detect anomaly. Many image segmentationtechniques are available in the literature. Computer Aided Diagnosing (CAD)system has been proposed in this paper for detection of foot bone anomaly bythe analysis of CT images. In this study, a segmentation based on edgedetection method is proposed for the classification of anomaly in foot CTimages. Edge detection algorithms are the most commonly used techniques inimage processing for edge detection. Canny edge... detector is evaluated in thispaper. (#br)We used “.dicom” medicalimage standard format and used ten male patient's foot CT images (245 imagesand 50 test data). The used parameters are detector collimation of 64 mm,scanning thickness of 1-5 mm, and pixel sizes of 512x512 in radiometric resolutionof 16 bits’ gray levels. (#br)The proposed methodconsists of five major steps: (i) calculating the horizontal & verticalgradient, (ii) determining gradient magnitude and gradient direction, (iii)applying non-maximal suppression, (iv) computing high and low thresholds, (v)hysteresis thresholding are applied to the multi-detector computed tomographyto detect the bone anomaly. (#br)In this study,automatic edge-based digital image processing techniques were applied to detectof foot bone anomaly. We proposed canny segmentation method that enables users tooquickly and efficiently segment anomaly in MDCT of foot. The resultsdemonstrate that the proposed segmentation method is effective for segmentinganomaly. The proposed method obtains satisfactory performances in terms ofaccuracy and F-measure the area under Receiver Operating Characteristic curve (ROCcurve (AUC)). We obtain an accuracy of 0.86 and F-measure of 0.92,respectively. (#br)Thepurpose of our study was to detect the anomaly of the foot and it was thesimplest and less time consuming process.