Search

Your search keyword '"Wu, Zhongke"' showing total 11 results
Start Over Author "Wu, Zhongke" Publisher hindawi limited
11 results on '"Wu, Zhongke"'

2. Craniofacial Reconstruction Evaluation by Geodesic Network

Author

Junli Zhao, Taorui Jia, Kang Wang, Quansheng Liu, Fuqing Duan, Wu Zhongke, Cuiting Liu, Beijing Normal University (BNU), Laboratoire de Mathématiques de Bretagne Atlantique (LMBA), and Université de Brest (UBO)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Adult, Similarity (geometry), Geodesic, Article Subject, Absolute value (algebra), lcsh:Computer applications to medicine. Medical informatics, General Biochemistry, Genetics and Molecular Biology, Young Adult, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, medicine, Image Processing, Computer-Assisted, Humans, Craniofacial, Aged, General Immunology and Microbiology, business.industry, Applied Mathematics, Skull, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Pattern recognition, General Medicine, Middle Aged, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Chin, Vertex (geometry), medicine.anatomical_structure, Feature (computer vision), Modeling and Simulation, Face (geometry), Face, lcsh:R858-859.7, Artificial intelligence, business, Psychology, Tomography, X-Ray Computed, Research Article
Abstract

Craniofacial reconstruction is to estimate an individual’s face model from its skull. It has a widespread application in forensic medicine, archeology, medical cosmetic surgery, and so forth. However, little attention is paid to the evaluation of craniofacial reconstruction. This paper proposes an objective method to evaluate globally and locally the reconstructed craniofacial faces based on the geodesic network. Firstly, the geodesic networks of the reconstructed craniofacial face and the original face are built, respectively, by geodesics and isogeodesics, whose intersections are network vertices. Then, the absolute value of the correlation coefficient of the features of all corresponding geodesic network vertices between two models is taken as the holistic similarity, where the weighted average of the shape index values in a neighborhood is defined as the feature of each network vertex. Moreover, the geodesic network vertices of each model are divided into six subareas, that is, forehead, eyes, nose, mouth, cheeks, and chin, and the local similarity is measured for each subarea. Experiments using 100 pairs of reconstructed craniofacial faces and their corresponding original faces show that the evaluation by our method is roughly consistent with the subjective evaluation derived from thirty-five persons in five groups.

Published
2014

Catalog

Books, media, physical & digital resources
See catalog results