Segmentasi Tulang Kortikal pada Citra Dental Panoramic Radiograph

Thohiroh Agus Kumala(1*), Agus Harjoko(2)

(2) Department of Computer Science and Electronics, Universitas Gadjah Mada
(*) Corresponding Author


Image processing in the medical world has been developed. One important stage in the processing of this image is segmentation. The accuracy in determining the diagnosis of a disease is determined by the accuracy of the segmentation stage.

This study used a dental panoramic radiograph image with the size of 2000x1000 pixels. The area of cortical bone samples taken from the cortical bone of the lower jaw right and left about the mental foramen with 128x128 pixels. To simplify the process of segmentation is carried out preprocessing on the image that is by contrast stretching and grayscale. Furthermore, image segmentation results of preprocessing conducted using active contour method. This method begins with the formation of the formation of the mask as the initial curve, from the initial curve is then the curve will move in or out according to the shape of the edge of the cortical bone.

Tests performed using the ROC (Receiver Operating Characteristic). Segmentation of 21 dental panoramic radiograph image data using Active Contour method can perform with the right cortical bone segmentation accuracy percentage of 90.67%, 90.14% sensitivity and 91.55% specificity. Cortical bone is left with an accuracy percentage of 89.37%, 86.59% sensitivity and 91.23% specificity.


active contour, dental panoramic radiograph, cortical bone, image segmentation

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[1] Arifin, A. Z., Asano, A., Taguchi, A., Nakamoto, T., Ohtsuka, M., Tsuda, M., Kudo, Y. and Tanimoto, K., 2006, Computer-aided System for Measuring the Mandibular Cortical Width on Dental Panoramic Radiographs in Identifying Postmenopausal Women With Low Bone Mineral Density, International Osteoporosis Foundation and National Osteoporosis Foundation, 17, 753–759

[2] Abidin, Z. dan Arifin, A. Z., 2009, Analisis Kerapatan Trabecular Bone Berbasis Graph Berbobot Pada Citra Panorama Gigi Untuk Identifikasi Osteoporosis, Jurnal TI, 7, 59-64

[3] Mardhiyah, A. dan Harjoko, A., 2011, Metode Segmentasi Paru-paru dan Jantung Pada Citra X-Ray Thorax, IJEIS, 1, 2, 35-44.

[4] Sprawls, P. (1995), The Physical Principles of Medical Imaging, 2nd edition, Medical Physics Pub. Corp.

[5] Fawcett, T. (2006), “An introduction to ROC analysis”, Pattern Recognition Letters, Vol. 27, hal. 861–874.

[6] Mohanty, A.K., Beberta, S., and Lenka, S.K. (2011), “Classifying Benign and Malignant Mass using GLCM and GLRLM based Texture Features from Mammogram”, International Journal of Engineering Research and Applications (IJERA), Vol. 1, hal. 687–693.


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