Abstract
This paper presents a knowledge-based image segmentation tool for organ delineation in CT (Computed Tomography) images. The noise and low contrast make the detection difficult. Therefore in this method, radial search, noise reduction method and post-processing algorithm have been implemented to improve the quality of contour detection. Three edge detection algorithms have been used and after detection several optimization methods have been employed to get the accurate contour from three detected contours. Finally to achieve higher accuracy of detection, active contour model (ACM), snake, has been used after the contour detected by previous methods.
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References
Haas, O.C.L.: Radiotherapy Treatment Planning: New System Approaches. Advances in Industrial Control Monograph, p. 220. Springer, London (1999) ISBN 1-85233-063-5
Meinzer, H.P., Thorn, M., Vetter, M., Hassenpflug, P., Wolf, I.: Medical imaging: examples of clinical applications. ISPRS Journal of Photogrammetry & Remote Sensing 56, 311–325 (2002)
Bueno, M.G.: Computer Aided Segmentation of Anatomical Structures in Computed Tomography Images, PhD thesis, Coventry University (1998)
Van den Berge, D.L., Ridder, M.D., Storme, G.A.: Imaging in radiotherapy. European Journal of Radiology 34, 41–48 (2000)
Vickers, J.P., Burnham, K.J., Dil, A., Haas, O.C.L., Mills, J.A.: Knowledge-Based Organ Segmentation in Low Contrast Medical Computed Tomography Images. In: Bubnicki, Z., Grzech, A. (eds.) Proc 14th Int. Conf. On Systems Science, Wroclaw (Pol), vol. 3, pp. 381–388 (2001)
Gonzalez, R.C., Woods, R.C.: Digital Image Processing. Addison-Wesley Publishing Company, Inc., Reading (1992)
Milios, E., Petrakis, E.: Shape Retrieval Based on Dynamic Programming. IEEE transactions on Image Processing, Special Issue on Image and Video Processing for Digital Libraries 9(1), 141–147 (2000)
Amini, A., Weymouth, T.E., Jain, R.C.: Using Dynamic Programming for Solving Variational Problems in Vision. IEEE transactions Pattern Analysis and Machine Intelligence 12(9) (1990)
Kang, D.J., Kim, C.Y., Seo, Y.S.: A Fast and Stable Method for Detecting and Tracking Medical Organs in MRI Sequences. IEICE Trans. Inf. & Syst. E82-D(2), 497–499 (1999)
Kass, M., Witkin, A., Terzopoulos, D.: Snake: Active Contour Models. International Journal of Computer Vision, 321–331 (1988)
Cohen, L.D.: On Active Contour Models and Balloons. CVGIP: Image Understanding 53(2), 211–218 (1991)
Xu, C., Prince, J.L.: Snakes, Shapes, and Gradient Vector Flow. IEEE transactions on Image Processing, 359–369 (1998)
Han, C.Y., Lin, K.N., Wee, W.G.: Knowledge-Based Image Analysis for Automated Boundary Extraction of Transesophageal Echocardiographic Left-Ventricular Images. IEEE transactions on Medical Imaging 10(4), 602–610 (1991)
Ruiz, E.E.S., Fairhurst, M.C.: Improved approach to boundary location in twodimentional echocardiographic images. IEE Proc.-Vis. Image Signal Process 142(3), 121–127 (1995)
Xu, W., Amin, S.A., Haas, O.C.L., Burnham, K.J., Mills, J.A.: Contour detection by using radial searching for CT images. In: Proc of the 4th Annual IEEE Conf. on Information Technology Applications in Biomedicine, UK, pp. 346–349 (2003)
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Xu, W., Amin, S.A., Haas, O.C.L., Burnham, K.J., Mills, J.A. (2004). Snake-Aided Automatic Organ Delineation. In: Rasmussen, C.E., Bülthoff, H.H., Schölkopf, B., Giese, M.A. (eds) Pattern Recognition. DAGM 2004. Lecture Notes in Computer Science, vol 3175. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28649-3_62
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DOI: https://doi.org/10.1007/978-3-540-28649-3_62
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