DocumentCode :
697911
Title :
Chan-Vese based method to segment mouse brain MRI images: Application to cerebral malformation analysis in Trisomy 21
Author :
Almhdie, Ahmad ; Lopes-Pereira, Patricia ; Meme, Sandra ; Colombier, Caroline ; Brault, Veronique ; Szeremeta, Frederic ; Doan, Bich-Thuy ; Ledee, Roger ; Harba, Rachid ; Herault, Yann ; Beloeil, Jean-Claude ; Leger, Christophe
Author_Institution :
PRISME, Univ. d´Orleans, Orléans, France
fYear :
2009
fDate :
24-28 Aug. 2009
Firstpage :
1883
Lastpage :
1887
Abstract :
A semi automatic active contour method based on Chan-Vese model is proposed for the segmentation of mouse brain MR images. First, a 2 ½ D strategy is applied on the axial images to segment the 3D volume of interest. The method takes into account the special shape of the object to segment. Moreover, the user defines the limits where to search these contours and also provides an initial contour. This semi automatic method makes that human intervention is limited and the tedious manual handling is greatly reduced. Results have shown that the brain volumes estimated by the method are identical to expert manually estimated volumes. Last but not least, the new method was used in the analysis of the cerebral malformations linked to Trisomy 21: no significant difference of the brain volumes between Trisomy 21 mice and the control ones were found.
Keywords :
biomedical MRI; brain; image segmentation; medical disorders; medical image processing; 2 ½ D strategy; 3D volume of interest; Chan-Vese based method; Trisomy 21 mice; axial images; brain volumes; cerebral malformation analysis; human intervention; initial contour; mouse brain MRI image segmentation; semiautomatic active contour method; Biological cells; Brain modeling; Image segmentation; Magnetic resonance imaging; Mice; Three-dimensional displays;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing Conference, 2009 17th European
Conference_Location :
Glasgow
Print_ISBN :
978-161-7388-76-7
Type :
conf
Filename :
7077483
Link To Document :
بازگشت