Statistical Deformable Model-Based Reconstruction of a Patient-Specific Surface Model from Single Standard X-ray Radiograph

被引:0
作者
Zheng, Guoyan [1 ]
机构
[1] Univ Bern, Inst Surg Technol & Biomech, CH-3014 Bern, Switzerland
来源
COMPUTER ANALYSIS OF IMAGES AND PATTERNS, PROCEEDINGS | 2009年 / 5702卷
关键词
point distribution model; statistical deformable 2D-3D registration; surface reconstruction; pelvis; REGISTRATION; IMAGES;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper; we present a hybrid 2D-3D deformable registration strategy combining a landmark-to-ray registration with a statistical shape; model-based 2D-3D reconstruction scheme; and show its application to reconstruct a patient-specific 3D surface model of the pelvis from single standard X-ray radiograph. The landmark-to-ray registration is used to find an initial scale and all initial rigid transformation between the X-ray image and the statistical shape model. The estimated scale and rigid transformation are then used to initialize the statistical shape model-based 2D-3D reconstruction scheme; which combines statistical instantiation and regularized shape deformation with an iterative image-to-model correspondence establishing algorithm. Quantitative and qualitative results of a feasibility study on clinical and cadaveric datasets are given, which indicate the validity of our approach.
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页码:672 / 679
页数:8
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