Title :
Medical image segmentation using texture directional features
Author :
Mavromatis, S. ; Boï, J.M. ; Sequeira, J.
Author_Institution :
Lab. d´´Informatique de Marseille, Marseilles Univ., Marseille, France
Abstract :
Medical image segmentation can often be performed through tissue texture analysis. One of the most recent and interesting ideas to do that is to take into account the distribution of local maximum orders. We have followed up this idea by using directional maximums and we have applied it to tissue differentiation. Two problems are emerging now: one is the identification of a given texture (labeling) and another one is the characterization of the different areas within images (segmentation). In this paper, we present our new approach for texture representation and analysis, and we point out the advances and problems involved in the image segmentation process.
Keywords :
biological tissues; image segmentation; image texture; medical image processing; different areas characterization; directional maximums; given texture identification; labeling; local maximum orders distribution; medical diagnostic imaging; medical image segmentation; texture directional features; tissue differentiation; Biomedical imaging; Entropy; Image analysis; Image segmentation; Image texture analysis; Labeling; Neodymium; Performance analysis; Pixel; Time measurement;
Conference_Titel :
Engineering in Medicine and Biology Society, 2001. Proceedings of the 23rd Annual International Conference of the IEEE
Print_ISBN :
0-7803-7211-5
DOI :
10.1109/IEMBS.2001.1017333