Nonlinear filtering of MR images using geometrically and statistically controlled diffusion

Author

Bajla, Ivan ; Witkovsky, Viktor ; Hanajik, Milan

Author_Institution

Inst. of Meas. Sci., Bratislava, Slovakia

fYear

1998

fDate

8-11 Sept. 1998

Firstpage

1

Lastpage

3

Abstract

In this paper a novel approach to the filtering of multivalued Magnetic Resonance (MR) images is proposed. The proposed method is essentially a nonlinear diffusion with a statistically and geometrically controlled conductance. The user is required to define samples of individual tissue classes in the input image, and their statistics are exploited during the image filtering. The method can be used in medical diagnostics for the enhancement and segmentation of medical images.

Keywords

biological tissues; biomedical MRI; image enhancement; image filtering; image segmentation; medical image processing; nonlinear filters; statistical analysis; MR images; geometrically-statistically controlled diffusion conductance; medical diagnostics; medical image enhancement; medical image segmentation; multivalued magnetic resonance images; nonlinear diffusion; nonlinear image filtering; tissue classes; Covariance matrices; Image edge detection; Image segmentation; Magnetic resonance; Medical diagnostic imaging; Probability;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Conference (EUSIPCO 1998), 9th European

Conference_Location

Rhodes

Print_ISBN

978-960-7620-06-4

Type

conf

Filename

7090065