干旱区生态环境知识资源中心(Arid): Level set segmentation with shape prior knowledge using intrinsic rotation, translation and scaling alignment

Arid

DOI	10.1016/j.bspc.2020.102241
	Level set segmentation with shape prior knowledge using intrinsic rotation, translation and scaling alignment
	Arrieta, Cristobal; Sing-Long, Carlos A.; Mura, Joaquin; Irarrazaval, Pablo; Andia, Marcelo E.; Uribe, Sergio; Tejos, Cristian
通讯作者	Arrieta, C
来源期刊	BIOMEDICAL SIGNAL PROCESSING AND CONTROL
ISSN	1746-8094
EISSN	1746-8108
出版年	2021
卷号	63
英文摘要	Level set segmentation has been successfully used in several image applications. However, they perform poorly when applied to severely corrupted images or when the object's boundaries are blurred or occluded. Poor performance can be improved by introducing shape prior knowledge into the segmentation process by considering additional shape information from training examples. This can be achieved by adding a regularization term that penalizes shapes that differ from those learned from a training database. This regularizer must be invariant under translation, rotation and scaling transformations. Previous works have proposed coupling the curve evolution to a registration problem through an optimization procedure. This approach is slow and its results depend on how this optimization is implemented. An alternative approach introduced an intrinsic alignment, which normalizes each shape to be compared on a common coordinate system, avoiding the registration process. Nevertheless, the proposed intrinsic alignment considered only scaling and translation but not rotation, which is critical in several image applications. In this paper we present a new method to incorporate shape prior knowledge based on the intrinsic alignment approach, but extending it for scaling, translation and rotation invariance. Our approach uses a regularization term based on the eigenvalues and eigenvectors of the covariance matrix of each training shape, and this eigendecomposition dependency leads to a new set of evolution equations. We tested our regularizer, combined with Chan-Vese, in 2D and 3D synthetic and medical images, demonstrating the effectiveness of using shape priors with intrinsic scaling, translation and rotation alignment in different segmentation problems.
英文关键词	Image segmentation Level sets Prior knowledge Pose invariance Intrinsic alignment
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000591530000010
WOS关键词	ACTIVE CONTOURS ; MEDICAL IMAGERY ; OASIS ; MODEL ; MRI
WOS类目	Engineering, Biomedical
WOS研究方向	Engineering
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/328011
作者单位	[Arrieta, Cristobal; Sing-Long, Carlos A.; Mura, Joaquin; Irarrazaval, Pablo; Andia, Marcelo E.; Uribe, Sergio; Tejos, Cristian] Pontificia Univ Catolica Chile, Biomed Imaging Ctr, Santiago, Chile; [Arrieta, Cristobal; Sing-Long, Carlos A.; Mura, Joaquin; Irarrazaval, Pablo; Andia, Marcelo E.; Uribe, Sergio; Tejos, Cristian] ANID Millennium Sci Initiat Program, Millennium Nucleus Cardiovasc Magnet Resonance, Santiago, Chile; [Sing-Long, Carlos A.; Irarrazaval, Pablo] Pontificia Univ Catolica Chile, Inst Biol & Med Engn, Santiago, Chile; [Sing-Long, Carlos A.] Pontificia Univ Catolica Chile, Inst Math & Computat Engn, Santiago, Chile; [Mura, Joaquin] Univ Tecn Federico Santa Maria, Dept Mech Engn, Santiago, Chile; [Irarrazaval, Pablo; Tejos, Cristian] Pontificia Univ Catolica Chile, Dept Elect Engn, Santiago, Chile; [Andia, Marcelo E.; Uribe, Sergio] Pontificia Univ Catolica Chile, Sch Med, Radiol Dept, Santiago, Chile; [Sing-Long, Carlos A.] ANID Millennium Sci Initiat Program, Millennium Nucleus Discover...
推荐引用方式 GB/T 7714	Arrieta, Cristobal,Sing-Long, Carlos A.,Mura, Joaquin,et al. Level set segmentation with shape prior knowledge using intrinsic rotation, translation and scaling alignment[J],2021,63.
APA	Arrieta, Cristobal.,Sing-Long, Carlos A..,Mura, Joaquin.,Irarrazaval, Pablo.,Andia, Marcelo E..,...&Tejos, Cristian.(2021).Level set segmentation with shape prior knowledge using intrinsic rotation, translation and scaling alignment.BIOMEDICAL SIGNAL PROCESSING AND CONTROL,63.
MLA	Arrieta, Cristobal,et al."Level set segmentation with shape prior knowledge using intrinsic rotation, translation and scaling alignment".BIOMEDICAL SIGNAL PROCESSING AND CONTROL 63(2021).