Book chapter
Volumetric Topological Analysis on In Vivo Trabecular Bone Magnetic Resonance Imaging
Advances in Visual Computing, pp.501-510
Lecture Notes in Computer Science, Springer International Publishing
2014
DOI: 10.1007/978-3-319-14249-4_47
Abstract
Osteoporosis is a common bone disease associated with increased risk of low-trauma fractures leading to substantial morbidity, mortality, and financial costs. Clinically, osteoporosis is defined by low bone mineral density (BMD); however, increasing evidence suggests that trabecular bone (TB) micro-architectural quality is an important determinant of bone strength and fracture risk. Recently developed volumetric topological analysis (VTA) is a unique method that characterizes individual trabeculae on the continuum between a perfect plate and a perfect rod. In this paper, an improved VTA algorithm is presented that eliminates the binarization step using fuzzy skeletonization. Its repeat scan reproducibility is evaluated for two different in vivo magnetic resonance imaging (MRI) protocols. High intra-class correlation coefficients, greater than 0.93, were observed for both the knee and the wrist MRI. The ability of the method to detect testosterone treatment effects of a two-year longitudinal study on hypogonadal men is also presented. Our method shows statistically significant improvement of TB quality as early as 6 months and the trend was observed to continue at 12 and 24 months.
Details
- Title: Subtitle
- Volumetric Topological Analysis on In Vivo Trabecular Bone Magnetic Resonance Imaging
- Creators
- Cheng Chen - University of IowaDakai Jin - University of IowaYinxiao Liu - University of IowaFelix W Wehrli - University of PennsylvaniaGregory Chang - New York UniversityPeter J Snyder - University of PennsylvaniaRavinder R Regatte - New York UniversityPunam K Saha - University of Iowa
- Resource Type
- Book chapter
- Publication Details
- Advances in Visual Computing, pp.501-510
- Publisher
- Springer International Publishing; Cham
- Series
- Lecture Notes in Computer Science
- DOI
- 10.1007/978-3-319-14249-4_47
- eISSN
- 1611-3349
- ISSN
- 0302-9743
- Language
- English
- Date published
- 2014
- Academic Unit
- Electrical and Computer Engineering; Radiology
- Record Identifier
- 9984197176202771
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