Variational segmentation of multi-channel MRI images

Author

Pien, Homer H. ; Gauch, John M.

Author_Institution

C.S. Draper Lab., Cambridge, MA, USA

Volume

3

fYear

1994

fDate

13-16 Nov 1994

Firstpage

508

Abstract

MRIs are effective for non-invasively imaging the interior of the human brain. Due to the large amount of data associated with typical MRI sessions, manual segmentation of the images of the human brain is prohibitive except in isolated cases. The various imaging and contrast artifacts common to MRIs, however, make automatic segmentation difficult. A segmentation algorithm incorporating multi-channel MRI data is described; this approach utilizes the variational calculus formulation to simultaneously compute piecewise smooth estimates of each channel, as well as a continuous “edge process” common to all the channels

Keywords

biomedical NMR; brain; edge detection; image segmentation; medical image processing; telecommunication channels; variational techniques; continuous edge process; contrast artifacts; human brain; imaging artifacts; multi-channel MRI images; multichannel MRI data; noninvasive imaging; piecewise smooth estimates; segmentation algorithm; variational calculus; variational segmentation; Biomedical imaging; Calculus; Computer science; Data mining; Educational institutions; Humans; Image segmentation; Laboratories; Magnetic resonance imaging; Robustness;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1994. Proceedings. ICIP-94., IEEE International Conference

Conference_Location

Austin, TX

Print_ISBN

0-8186-6952-7

Type

conf

DOI

10.1109/ICIP.1994.413754

Filename

413754