Automated segmentation of CBCT image using spiral CT atlases and convex optimization.
Automated segmentation of CBCT image using spiral CT atlases and convex optimization.
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DOI:
10.1007/978-3-642-40760-4_32
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发表时间:
2013
期刊:
影响因子:
--
通讯作者:
Shen, Dinggang
中科院分区:
文献类型:
--
作者:
Wang, Li;Chen, Ken Chung;Shi, Feng;Liao, Shu;Li, Gang;Gao, Yaozong;Shen, Steve G. F.;Yan, Jin;Lee, Philip K. M.;Chow, Ben;Liu, Nancy X.;Xia, James J.;Shen, Dinggang
Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. CBCT scans have relatively low cost and low radiation dose in comparison to conventional spiral CT scans. However, a major limitation of CBCT scans is the widespread image artifacts such as noise, beam hardening and inhomogeneity, causing great difficulties for accurate segmentation of bony structures from soft tissues, as well as separating mandible from maxilla. In this paper, we presented a novel fully automated method for CBCT image segmentation. In this method, we first estimated a patient-specific atlas using a sparse label fusion strategy from predefined spiral CT atlases. This patient-specific atlas was then integrated into a convex segmentation framework based on maximum a posteriori probability for accurate segmentation. Finally, the performance of our method was validated via comparisons with manual ground-truth segmentations.
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影响因子:
10.6
作者:
Rousseau F;Habas PA;Studholme C
通讯作者:
Studholme C
DOI:
10.1007/978-3-642-33454-2_48
发表时间:
2012
期刊:
LECTURE NOTES IN ARTIFICIAL INTELLIGENCE
影响因子:
--
作者:
Liao, Shu;Gao, Yaozong;Shen, Dinggang
通讯作者:
Shen, Dinggang
DOI:
10.1016/j.tripleo.2005.10.039
发表时间:
2006-08-01
影响因子:
--
作者:
Loubele, Miet;Maes, Frederik;Suetens, Paul
通讯作者:
Suetens, Paul
DOI:
10.1109/tpami.2008.79
发表时间:
2009-02-01
影响因子:
23.6
作者:
Wright, John;Yang, Allen Y.;Ma, Yi
通讯作者:
Ma, Yi
影响因子:
19.5
作者:
Caselles, V;Kimmel, R;Sapiro, G
通讯作者:
Sapiro, G