TY - GEN
T1 - 3D segmentation of rodent brain structures using Active Volume Model with shape priors
AU - Zhang, Shaoting
AU - Huang, Junzhou
AU - Uzunbas, Mustafa
AU - Shen, Tian
AU - Delis, Foteini
AU - Huang, Xiaolei
AU - Volkow, Nora
AU - Thanos, Panayotis
AU - Metaxas, Dimitris
N1 - Copyright:
Copyright 2011 Elsevier B.V., All rights reserved.
PY - 2011
Y1 - 2011
N2 - Object boundary extraction is an important task in brain image analysis. Acquiring detailed 3D representations of the brain structures could improve the detection rate of diseases at earlier stages. Deformable model based segmentation methods have been widely used with considerable success. Recently, 3D Active Volume Model (AVM) was proposed, which incorporates both gradient and region information for robustness. However, the segmentation performance of this model depends on the position, size and shape of the initialization, especially for data with complex texture. Furthermore, there is no shape prior information integrated. In this paper, we present an approach combining AVM and Active Shape Model (ASM). Our method uses shape information from training data to constrain the deformation of AVM. Experiments have been made on the segmentation of complex structures of the rodent brain from MR images, and the proposed method performed better than the original AVM.
AB - Object boundary extraction is an important task in brain image analysis. Acquiring detailed 3D representations of the brain structures could improve the detection rate of diseases at earlier stages. Deformable model based segmentation methods have been widely used with considerable success. Recently, 3D Active Volume Model (AVM) was proposed, which incorporates both gradient and region information for robustness. However, the segmentation performance of this model depends on the position, size and shape of the initialization, especially for data with complex texture. Furthermore, there is no shape prior information integrated. In this paper, we present an approach combining AVM and Active Shape Model (ASM). Our method uses shape information from training data to constrain the deformation of AVM. Experiments have been made on the segmentation of complex structures of the rodent brain from MR images, and the proposed method performed better than the original AVM.
UR - http://www.scopus.com/inward/record.url?scp=80055059194&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80055059194&partnerID=8YFLogxK
U2 - 10.1109/ISBI.2011.5872439
DO - 10.1109/ISBI.2011.5872439
M3 - Conference contribution
AN - SCOPUS:80055059194
SN - 9781424441280
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 433
EP - 436
BT - 2011 8th IEEE International Symposium on Biomedical Imaging
T2 - 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11
Y2 - 30 March 2011 through 2 April 2011
ER -