Morphological Exponential Entropy Driven-HUM

Author

Ardizzone, Edoardo ; Pirrone, Roberto ; Gambino, Orazio

Author_Institution

Dept. of Comput. Sci., Palermo Univ.

fYear

2006

fDate

Aug. 30 2006-Sept. 3 2006

Firstpage

3771

Lastpage

3774

Abstract

This paper presents an improvement to the exponential entropy driven-homomorphic unsharp masking (E²D-HUM) algorithm devoted to illumination artifact suppression on magnetic resonance images. E²D-HUM requires a segmentation step to remove dark regions in the foreground whose intensity is comparable with background, because strong edges produce streak artifacts on the tissues. This new version of the algorithm keeps the same good properties of E²D-HUM without a segmentation phase, whose parameters should be chosen in relation to the image

Keywords

biomedical MRI; brain; filtering theory; image segmentation; medical image processing; artifact suppression; brain; dark region removal; homomorphic unsharp masking; magnetic resonance images; morphological exponential entropy; segmentation step; streak artifacts; tissues; Cutoff frequency; Entropy; Filtering; Filters; Image segmentation; Lighting; Magnetic resonance; Magnetic resonance imaging; Pixel; Surface fitting;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE

Conference_Location

New York, NY

ISSN

1557-170X

Print_ISBN

1-4244-0032-5

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/IEMBS.2006.259318

Filename

4462620