Paper Info
Title
Registration of knee joint surfaces for the in vivo study of joint injuries based on magnetic resonance imaging.
Abstract
In-vivo quantitative assessments of joint conditions and health status can help to increase understanding of the pathology of osteoarthritis, a degenerative joint disease that affects a large population each year. Magnetic resonance imaging (MRI) provides a non-invasive and accurate means to assess and monitor joint properties, and has become widely used for diagnosis and biomechanics studies. Quantitative analyses and comparisons of MR datasets require accurate alignment of anatomical structures, thus image registration becomes a necessary procedure for these applications. This research focuses on developing a registration technique for MR knee joint surfaces to allow quantitative study of joint injuries and health status. It introduces a novel idea of translating techniques originally developed for geographic data in the field of photogrammetry and remote sensing to register 3D MR data. The proposed algorithm works with surfaces that are represented by randomly distributed points with no requirement of known correspondences. The algorithm performs matching locally by identifying corresponding surface elements, and solves for the transformation parameters relating the surfaces by minimizing normal distances between them. This technique was used in three applications to: 1) register temporal MR data to verify the feasibility of the algorithm to help monitor diseases, 2) quantify patellar movement with respect to the femur based on the transformation parameters, and 3) quantify changes in contact area locations between the patellar and femoral cartilage at different knee flexion angles. The results indicate accurate registration and the proposed algorithm can be applied for in-vivo study of joint injuries with MRI.
Year
DOI
Venue
2006
10.1117/12.653518
Proceedings of SPIE
Keywords
Field
DocType
registration,surface matching,magnetic resonance,knee,osteoarthritis,injuries
Biomedical engineering,Population,Photogrammetry,Computer vision,Osteoarthritis,Femur,Knee Joint,Artificial intelligence,Biomechanics,Geography,Image registration,Magnetic resonance imaging
Conference
Volume
ISSN
Citations 
6144
0277-786X
0
PageRank 
References 
Authors
0.34
2
4
Name
Order
Citations
PageRank
Rita W. T. Cheng100.34
Ayman Habib235639.62
Richard Frayne3398.71
Janet L Ronsky4174.51