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Abstrakty
In this paper, it is shown that pathological changes of vascular networks, inside an extensive organ, influence textures observed on medical images. A 3D, dynamic model of the organ and its vascular system was developed, and it enables to control the tissue perfusion. To render CT scan-like images, the acquisition process was also modeled. The proposed approach is applied to simulate the development of the hepatic vascular system and to induce hyper- and hypo-vascularized lesions inside the liver. The texture analysis of the obtained images is then performed. It shows that textural features can characterize regions changed by pathological processes as far as the acquisition conditions are precisely are presicely controlled.
Wydawca
Czasopismo
Rocznik
Tom
Strony
65--79
Opis fizyczny
Bibliogr. 23 poz., rys., tab., wykr.
Twórcy
autor
- Departament of Computer Science, Technical University of Białystok, Poland; Laboratoire Traitement du Signal et de l'Image, INSERM, Universite de Rennes, France
autor
- Laboratoire Traitement du Signal et de l'Image, INSERM, Universite de Rennes, France
Bibliografia
- [1] Bruno A.. Collorec R„ Bezy-Wendling J., Reuze P., Rolland Y.: Texture analysis in medical imaging, in: Contemporary Perspectives in Three-dimensional Biomedical imaging. C. Roux and J.L. Coatrieux (Eds.), IOS Press, 1997, 133-164.
- [2] Herlidou S„ Rolland Y„ Bansard J.Y., Le Ruleur E„ de Certaines J.D, Comparison of automated and visual texture analysis in MRI: Characterization of normal and diseased skeletal muscle. Magnetic Resonance Imaging 1999, 17, 9, 1393-1397.
- [3] Lefebvre F„ Meunier M„ Thibault F., Laugier R, Berger G.: Computerized ultra-characterization of breast nodules. Ultrasound in Medicine and Biolog v 2000, 26, 9, 1421-1428.
- [4] Chappard D., Chennebault A., Moreau M., Legrand E., Audran M., Basle M.F.: Texture analysis of X-ray radiograms is a more reliable descriptor of bone loss than mineral content in a rat model of localized disuse induced by the Clostridium botulinum toxin. Bone 2001, 28, 1, 72-79.
- [5] McNitt-Gray M.F., Wyckoff N., Sayre J.W., Goldin J.G., Aberle D.R.: The effects of co-occurrence matrix based texture parameters on the classification of solitary pulmonary nodules imaged oil computed tomography. Computerized Medical Imaging and Graphics 1999, 23, 339-348.
- [6] Vince D.G., Dixon K.J., Cothren R.M., Cornhill J.F.: Comparison of texture analysis methods for the characterization of coronary plaques in intravascular ultrasound images. Computerized Medical Imaging and Graphics 2000, 24, 221-229.
- [7] Murray C.D.: The physiological principle of minimum work applied to the angle of branching arteries. J. Gen. Physiol 1926, 9, 835-841.
- [8] Gottlieb M.E.: Modeling blood vessels: a deterministic method with fractal structure based on physiological rules. Proc. Int. Conf. of the IEEE Engineering in Medicine and Biology Society 1990, 12, 3, 1386-1987.
- [9] Schreiner W., Buxbaum P.F.: Computer optimization of vascular trees. IEEE transactions on Biomedical Engineering 1993, 40, 5, 482-491.
- [10] Nekka F., Kyriacos S., Kerrigan C., Cartilier L.: A model of growing vascular structures. Bull. Math. Biol. 1996, 58, 3, 409-424.
- [11] Karch R., Neumann F., Neumann M., Schreiner W.: A three-dimensional model for arterial tree representation, generated by constrained constructive optimization. Computers in Biology and Medicine 1999, 29, 19-38.
- [12] Bezy-Wendling J., Bruno A.: A 3-D dynamic model of vascular trees. Journal of Biological Systems 1999, 7, 1, 11-31.
- [13] Rolland Y., Bezy-Wendling J., Duvauferrier R., Coatrieux J.L.: Slice simulation from a model of the parenchymous vascularization to evaluate texture features. Investigative Radiology 1999, 34, 3, 181-184.
- [14] Bezy-Wendling J., Krętowski M., Rolland Y., Le Bidon W.: Toward a better understanding of texture in vascular CT scan simulated image. IEEE Transactions on Biomedical Engineering 2001, 48, 1, 120-124.
- [15] Hudlicka O., Brown M.D., Egginton S.: Angiogenesis: basic concepts and methodology. In: An Introduction to Vascular Biology, edited by A. Halhclay, B.J. Hunt, L. Poston and M. Schachter, Cambridge University Press, 1998, 3-19.
- [16] Zamir M.: Optimality principles in arterial branching. J. Theor. Biol. 1976, 62, 227-251.
- [17] Changizi M.A., Cherniak C.: Modeling the large-scale geometry of human coronary arteries. Can. J. Physiol. Pharmacol. 2000, 78, 603-611.
- [18] Kamiya A., Togawa T.: Optimal branching structure of the vascular trees. Bulletin of Mathematical Biophysics 1972, 34, 431-438.
- [19] Krętowski M„ Rolland Y., Bezy-Wendling J., Coatrieux J.L.: Fast algorithm for 3-D vascular-tree modeling. Computer Methods and Programs in Biomedicine (in print).
- [20] Herman G.T.: Image Reconstruction from Projections, The Fundamentals of Computerized Tomography. Computer Science and Applied Mathematics, 1980.
- [21] Kak A.C., Slaney M.: Principles of Computerized Tomographic Imaging. IEEE Press, 1988.
- [22] Haralick R.M., Shanmugam K., Dinstein I.: Textural features for image classification. IEEE Transactions on Systems, Man and Cybernetics 1973, 3, 610-621.
- ]23] Haralick R.M.: Statistical and structural approaches to texture. Proceedings ol the IEEE 1979, 67, 5, 786-804.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPZ1-0003-0038