(14-15(01)) * << * >> * Russian * English * Content * All Issues

Algorithms for nonlinear smoothing of MR brain images by non-isotropic diffusion
I. Bajla
Institute of Measurement Science, Slovak Academy of Sciences, Dubravska cesta 9, 842 19 Bratis1ava, Slovak Republic

 PDF, 3195 kB

Pages: 97-112.

Full text of article: Russian language.

Abstract:
In magnetic resonance imaging (tomography based on nuclear magnetic resonance) being one of the fastest growing areas of medical introscopy, the researchers have recently paid significant attention to fast methods for collecting MR data. Among other reasons motivating this interest, the following two seem to be especially important:
1) elimination or minimization of the influence of artifacts arising from the movement of organs,
2) formation of a sufficient amount of data necessary for three-dimensional (3D) image visualization within a period of time acceptable for the medicine (minutes).

Citation:
Bajla I. Algorithms for nonlinear smoothing of MR brain images by non-isotropic diffusion. Computer Optics 1995; 14-15(1): 97-112.

References:
  1. Bomans М et al. 3-D segmentation of MR images of the head for 3-D display. IEEE Trans, on Medical Imaging; MI 9 (2): 177- 183; 1990.
  2. Stanier J et al. Segmentation schemes for knowledge-based construction of individual atlases from slice-type medical images. Proc. of SPIE; 1993; 1898: Image Processing: 252-262.
  3. Perona P, Malik J. Scale-space and edge detection using anisotropic diffusion. IEEE Trans, on Pattern Analysis and Machine Intelligence; 1990; PAMI 12 (7): 629-639.
  4. Gerig G et al. Nonlinear anisotropic filtering of MRI Data. IEEE Trans, on Medical Imaging; 1992; MI 11 (2): 221-232.
  5. Canny J. A computational approach to edge detection. IEEE Trans, on Pattern Analysis and Machine Intelligence; 1986; PAMI 8: 679-698.
  6. Gonzalez RC, Woods RE. Digital image processing. Addison-Wesley, Reading, 1992.
  7. Bajla I et al. Anisotropic filtering of MRI data based upon image gradient histogram. Ed. by Chetverikov D, Kropatsch WG. Proc. of CAIP'93-Computer Analysis of Images and Patterns, Springer-Verlag, Berlin: 1993; 90-97.
  8. Shrinivasan V et al. Image reconstruction by a Hopfield neural network. Image and Vision Computing; 1993 11(5): 278-281.
  9. Shepp LA, Logan BF. The Fourier reconstruction of a head section. IEEE Trans, on Nucl. Sci.; 1974; NS-21(3): 21-24 .

© 2009, IPSI RAS
151, Molodogvardeiskaya str., Samara, 443001, Russia; E-mail: journal@computeroptics.ru ; Tel: +7 (846) 242-41-24 (Executive secretary), +7 (846) 332-56-22 (Issuing editor), Fax: +7 (846) 332-56-20