DocumentCode :
2025608
Title :
Shape Prior Integrated in an Automated 3D Region Growing Method
Author :
Rose, J.-L. ; Revol-Muller, Ch. ; Almajdub, Mo ; Chereul, Em ; Odet, Ch.
Author_Institution :
Univ. Claude Bernard Lyon1, Villeurbanne
Volume :
1
fYear :
2007
fDate :
Sept. 16 2007-Oct. 19 2007
Abstract :
We propose a new automated region growing method integrating shape prior (RGISP). The aim of this work is to improve region growing segmentation by taking into account a reference model. Our algorithm is assessed on a synthesized image and compared with two other methods in order to point up the contribution of shape prior. It was also applied to segment in-vivo mu-CT images of mouse kidneys in the framework of small animal imaging. RGISP gives promising results and appears to be well adapted to satisfy small animal imaging constraints.
Keywords :
computerised tomography; image segmentation; medical image processing; animal imaging constraints; automated 3D region growing method; mouse kidneys; mu-CT images; region growing segmentation; Animals; Biomedical imaging; Feature extraction; Image processing; Image segmentation; Mice; Noise shaping; Shape; Solid modeling; Testing; Image processing; image segmentation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 2007. ICIP 2007. IEEE International Conference on
Conference_Location :
San Antonio, TX
ISSN :
1522-4880
Print_ISBN :
978-1-4244-1437-6
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2007.4378889
Filename :
4378889
Link To Document :
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