Name
Abstract | ||
|---|---|---|
We present an algorithm for the segmentation of the liver in 2-D computed tomography slice images. The basis for our algorithm is an implicit active shape model. In order to detect the liver boundary and guide the shape model deformation, a boundary classifier has been integrated into the implicit framework in a novel manner The accuracy of the algorithm has been evaluated for 20 test cases including both normal and abnormal livers. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/ICPR.2008.4760968 | 19TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOLS 1-6 |
Keywords | Field | DocType |
level set,active shape model,computed tomography,image segmentation,image classification,shape | Active shape model,Computer vision,Pattern recognition,Segmentation,Computer science,Level set,Image segmentation,Artificial intelligence,Computed tomography,Test case,Classifier (linguistics),Contextual image classification | Conference |
ISSN | Citations | PageRank |
1051-4651 | 4 | 0.49 |
References | Authors | |
5 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andreas Wimmer | 1 | 334 | 18.57 |
| Joachim Hornegger | 2 | 1734 | 190.62 |
| Grzegorz Soza | 3 | 386 | 24.12 |