Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Model base for craniofacial reconstruction and craniofacial reconstruction method

A model library and craniofacial technology, applied in 3D modeling, image data processing, instruments, etc., can solve the problem of low representation ability of statistical deformable models

Active Publication Date: 2013-08-21
NORTHWEST UNIV(CN)
View PDF4 Cites 29 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] One of the purposes of the present invention is to provide a model library for craniofacial restoration, which is established by using a method for establishing a craniofacial local shape relationship model library based on PLSR local shape relationship modeling to solve craniofacial problems based on statistical theory. Face restoration methods face the problems of low representation ability of statistical deformable models, small sample problems and multiple correlation problems of variables, so as to improve the scientificity and accuracy of craniofacial restoration

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Model base for craniofacial reconstruction and craniofacial reconstruction method
  • Model base for craniofacial reconstruction and craniofacial reconstruction method
  • Model base for craniofacial reconstruction and craniofacial reconstruction method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0287] This embodiment is based on the craniofacial database formed by the complete set of tomographic imaging data of a large number of living craniofacial samples collected by a spiral CT (Computer Tomography) machine, wherein the CT machine scans the human head every 1.5mm , to obtain a set of tomographic imaging data consisting of about 200 to 300 CT images, using the craniofacial restoration model library of the present invention for such as Figure 5 (a) The skull to be restored is restored. In this example, L=10 in step (3.1), and Q in step (4.3.2) 1 =15, J=4 in step (4.3), λ in step (4.3.7) j = 1 / 4 (where j=1,2,3,4), α=0.05 in step 7, the restoration result is as follows Figure 5 (c) shown.

[0288] Figure 2 is a schematic diagram of the encoding and position calibration of the facial skin and skull feature points in this embodiment, and the round spheres on the surface of the model represent the feature points, where Figure 2 (a) is a schematic diagram of the e...

Embodiment 2

[0293] This embodiment is based on the craniofacial database formed by the complete set of tomographic imaging data of a large number of living craniofacial samples collected by a spiral CT (Computer Tomography) machine, wherein the CT machine scans the human head every 1.5mm , obtain a set of tomographic imaging data consisting of about 200-300 CT images, adopt the road surface restoration model library of the present invention for such as Image 6 (a) The skull to be restored is restored. In this example, L=10 in step (3.1), and Q in step (4.3.2) 1 =15, J=4 in step (4.3), λ in step (4.3.7) j = 1 / 4 (where j=1,2,3,4), α=0.05 in step 7;

[0294] The restored result is as Image 6 (c), in contrast to that, Image 6 (b) is the facial restoration result based on the zonal statistical model, Image 6 (d) is the three-dimensional surface model of the original skin corresponding to the skull to be restored.

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a model base for craniofacial reconstruction and a craniofacial reconstruction method. The model base for craniofacial reconstruction comprises a craniofacial standard model base and a craniofacial PLSR shape relation model base, wherein physiological points are defined on the craniofacial standard model base. According to the craniofacial reconstruction method, a craniofacial three-dimensional surface model base, on which physiological point corresponding relations are defined, is established through a skin layer point correspondence method and a skull point correspondence method, wherein the skin layer point correspondence method combines partition deformation and multiple restrictions, and the skull point correspondence method is base on TPS overall deformation and multiple restrictions. A craniofacial partial shape relation model based on PLSR is established on the basis of the craniofacial three-dimensional surface model base, and thus the craniofacial PLSR shape relation model base is obtained. By means of a craniofacial standard model, which has the same forensic anthropological information with a to-be-reconstructed skull, in the craniofacial reconstruction model base and the craniofacial PLSR shape relation model, the face of the skull is reconstructed. The craniofacial reconstruction model base is established in the craniofacial partial shape relation modeling method based on PLSR, and the problems that samples are small and variables have multiple correlations in the craniofacial reconstruction method based on statistical theory are solved.

Description

technical field [0001] The invention belongs to the field of computer image graphics processing, and in particular relates to a craniofacial restoration model library and a craniofacial restoration method. Background technique [0002] Craniofacial restoration is a technique to infer and predict the original appearance of the unknown skull based on the internal growth and change law between the skull and the appearance. How to establish a statistical calculation model of craniofacial morphology relationship with high-efficiency prediction ability is a key problem to be solved in craniofacial reconstruction based on statistics. [0003] In 2005, Maxime et al. innovatively introduced statistical models into the craniofacial restoration process, and proposed a new craniofacial restoration method based on statistical deformable models for the first time. The craniofacial restoration based on the statistical deformable model adopts the principal component analysis method, and es...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06T17/30
Inventor 贺毅岳耿国华周明全高妮贾甲茹少峰贺小伟高原李康史哲
Owner NORTHWEST UNIV(CN)
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com