Automatic segmentation of cardiac images: texture mapping

Author

Fortin, C. ; Ohley, W. ; Gewirtz, H.

Author_Institution

Dept. of Electr. Eng., Rhode Island Univ., Kingston, RI, USA

fYear

1991

fDate

4-5 Apr 1991

Firstpage

202

Lastpage

203

Abstract

Image texture is used to segment left ventricular magnetic resonance (MR) images. The approach is built upon assumptions regarding those probability density functions (PDFs) present within the image. Specifically, an algorithm is constructed which assumes that the data are distributed as fractional Brownian motion (FBM). The FBM is parameterized by H, which quantifies the roughness present in the image texture. When the algorithm is applied to MR data, a bimodal histogram results. This allows automatic classification of the data with resulting LV segmentation

Keywords

biomedical NMR; cardiology; computerised picture processing; medical diagnostic computing; algorithm; automatic classification; automatic image segmentation; bimodal histogram; cardiac images; fractional Brownian motion; left ventricular magnetic resonance images; medical diagnostic imaging; probability density functions; roughness; texture mapping; Blood; Density functional theory; Histograms; Hospitals; Humans; Image segmentation; Image texture; Magnetic resonance; Maximum likelihood estimation; Pixel;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioengineering Conference, 1991., Proceedings of the 1991 IEEE Seventeenth Annual Northeast

Conference_Location

Hartford, CT

Print_ISBN

0-7803-0030-0

Type

conf

DOI

10.1109/NEBC.1991.154645

Filename

154645