Superimposition of Cone-Beam Computed Tomography Images by Joint   Embedding

doi:10.1109/TBME.2016.2598584

CORC > 北京大学 > 信息科学技术学院

	Superimposition of Cone-Beam Computed Tomography Images by Joint Embedding
	Pei, Yuru ; Ma, Gengyu ; Chen, Gui ; Zhang, Xiaoyun ; Xu, Tianmin ; Zha, Hongbin
刊名	IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
	2017
关键词	CBCT image superimposition joint embedding subset extraction MUTUAL-INFORMATION BIMAXILLARY SURGERY REGISTRATION SEGMENTATION MAXIMIZATION
DOI	10.1109/TBME.2016.2598584
英文摘要	Objective: The superimposition of cone-beam computed tomography (CBCT) images is an essential step to evaluate shape variations of pre and postorthodontic operations due to pose variations and the bony growth. The aim of this paper is to present and discuss the latest accomplishments in voxel-based craniofacial CBCT superimpositions along with structure discriminations. Methods: We propose a CBCT superimposition method based on joint embedding of subsets extracted from CBCT images. The subset is defined at local extremes of the first-order difference of Gaussian-smoothed volume images to reduce the data involved in the computation. A rotation-invariant integral operator is proposed as the context-aware textural descriptor of subsets. We cope with subset correspondences by joint embedding with matching identifications in manifolds, which take into account the structure of subsets as a whole to avoid mapping ambiguities. Once given subset correspondences, the rigid transformations, as well as the superimposition of volume images, are obtained. Our system allows users to specify the structure-of-interest based on a semisupervised label propagation technique. Results: The performance of the proposed method is evaluated on ten pairs of pre and postoperative CBCT images of adult patients and ten pairs of growing patients, respectively. The experiments demonstrate that the craniofacial CBCT superimposition can be performed effectively, and outperform state of the arts. Conclusion: The integration of sparse subsets with context-aware spherical intensity integral descriptors and correspondence establishment by joint embedding enables the reliable and efficient CBCT superimposition. Significance: The potential of CBCT superimposition techniques discussed in this paper is highlighted and related challenges are addressed.; National Natural Science Foundation of China [61272342]; Seeding Grant for Medicine and Information Sciences of Peking University [2014MI24]; SCI(E); ARTICLE; 6; 1218-1227; 64
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/473167]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Pei, Yuru,Ma, Gengyu,Chen, Gui,et al. Superimposition of Cone-Beam Computed Tomography Images by Joint Embedding[J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING,2017.
APA	Pei, Yuru,Ma, Gengyu,Chen, Gui,Zhang, Xiaoyun,Xu, Tianmin,&Zha, Hongbin.(2017).Superimposition of Cone-Beam Computed Tomography Images by Joint Embedding.IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING.
MLA	Pei, Yuru,et al."Superimposition of Cone-Beam Computed Tomography Images by Joint Embedding".IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING (2017).