Document Detail


Contour-Based Surface Reconstruction using MPU Implicit Models.
MedLine Citation:
PMID:  18496609     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
This paper presents a technique for creating a smooth, closed surface from a set of 2D contours, which have been extracted from a 3D scan. The technique interprets the pixels that make up the contours as points in R(3) and employs Multi-level Partition of Unity (MPU) implicit models to create a surface that approximately fits to the 3D points. Since MPU implicit models additionally require surface normal information at each point, an algorithm that estimates normals from the contour data is also described. Contour data frequently contains noise from the scanning and delineation process. MPU implicit models provide a superior approach to the problem of contour-based surface reconstruction, especially in the presence of noise, because they are based on adaptive implicit functions that locally approximate the points within a controllable error bound. We demonstrate the effectiveness of our technique with a number of example datasets, providing images and error statistics generated from our results.
Authors:
Ilya Braude; Jeffrey Marker; Ken Museth; Jonathan Nissanov; David Breen
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Publication Detail:
Type:  JOURNAL ARTICLE    
Journal Detail:
Title:  Graphical models     Volume:  69     ISSN:  1524-0703     ISO Abbreviation:  Graph Models     Publication Date:  2007 Mar 
Date Detail:
Created Date:  2009-3-5     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101137122     Medline TA:  Graph Models     Country:  -    
Other Details:
Languages:  ENG     Pagination:  139-157     Citation Subset:  -    
Affiliation:
Department of Computer Science, Drexel University, Philadelphia, PA.
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MeSH Terms
Descriptor/Qualifier:
Grant Support
ID/Acronym/Agency:
U24 RR021760-02//NCRR NIH HHS

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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