A multistep approach for micro tomography obtained medical image segmentation

• Autorzy: Buczkowski M. , Saeed K.
• Języki publikacji: EN

Abstrakty

EN

This paper presents a multistep approach for segmentation of micro tomography images. Various images of porous structures were studied. Proper segmentation of that images is necessary to create 3D models of these structures. The introduced algorithm concerns finding the proper way of image filtering before the use of Canny-Deriche edge detection to obtain the best possible segmentation.

Słowa kluczowe

EN

image segmentation; bilateral filter; Canny-Deriche edge detector; microtomography; porous materials

PL

segmentacja obrazu; filtr dwustronny; wykrywanie krawędzi; mikrotomografia; materiały porowate

• Wydawca: University of Silesia, Institute of Informatics, Computer Systems Department
• Czasopismo: Journal of Medical Informatics & Technologies
• Rocznik: 2014
• Tom: Vol. 23
• Strony: 69--76
• Opis fizyczny: Bibliogr. 13 poz., rys.

Twórcy

autor

Buczkowski M.

• Faculty of Physics and Applied Computer Science AGH University of Science and Technology, Krakow, Poland

autor

Saeed K.

• Faculty of Physics and Applied Computer Science AGH University of Science and Technology, Krakow, Poland
• Faculty of Computer Science, Bialystok University of Technology, Bialystok, Poland

Bibliografia

• [1] BUCZKOWSKI M., SAEED K., TARASIUK J., WROSKI S., KOSIOR J., In: R. Chaki et al. (eds.), Applied Computation and Security Systems, Advances in Intelligent Systems and Computing 304, 2014.
• [2] CANNY J., A computational approach to edge detection. Pattern Analysis and Machine Intelligence, IEEE Transactions on 6, 1986, pp. 679-698.
• [3] DERICHE R., Using Canny’s criteria to derive a recursively implemented optimal edge detector. International journal of computer vision 1.2, 1987, pp. 167-187.
• [4] FELDKAMP LA, DAVIS LC, KRESS JW, Practical cone-beam algorithm. J Opt Soc Am, A6, 1984, pp. 612-9.
• [5] HE LEI, ET AL, A comparative study of deformable contour methods on medical image segmentation. Image and Vision Computing 26.2, 2008, pp. 141-163.
• [6] JAHNE B., Digital Image Processing: Concept, Algorithms, and Scientific Applications. Springer, 1997.
• [7] PARIS S., KORNPROBST P., TUMBLIN J., DURAND F., Bilateral Filtering: Theory and Applications. Foundations and Trends in Computer Graphics and Vision, 2008, Vol. 4, No. 1, pp. 173.
• [8] RADON J., Uber die Bestimmung von Funktionen durch ihre Integralwerte Langs Gewisser Mannigfaltigkeiten. Ber. Saechsische Akad. Wiss. 29, 1917, pp. 262.
• [9] ROGOWSKA J., Overview and fundamentals of medical image segmentation. Handbook of medical imaging, Academic Press, Inc., 2000, pp. 69-85.
• [10] SAEED K., ALBAKOOR M., Region Growing Based Segmentation Algorithm for Typewritten, and Handwritten Text Recognition. Applied Soft Computing, Elsevier Science Publishers, 2009, Vol. 9 , No. 2, pp. 608-617.
• [11] SEZGIN M., SANKUR B., Survey over image thresholding techniques and quantitative performance evaluation, Journal of Electronic Imaging 13(1), 2004, pp. 146165.
• [12] XU C., PHAM L. D., PRINCE J. L., Image segmentation using deformable models. Handbook of medical imaging 2, 2000, pp. 129-174.
• [13] VOLUME GRAPHICS GMBH, EDITOR, Reference Manual VGStudio Max Release 2.0; http://www.volumegraphics.com/en/products/vgstudio-max/ 8.10.2013