| 1. |
- Borga, Magnus, 1965-, et al.
(author)
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MRI-Based Body Composition Analysis
- 2022. - 1
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In: Basic Protocols in Foods and Nutrition. - New York, NY, United States : Springer Nature. - 9781071623442 ; , s. 307-334
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Book chapter (peer-reviewed)abstract
- Magnetic resonance imaging (MRI) is considered being state-of-the-art technology for body composition analysis. Compared to other indirect techniques such as scales, calipers, bioimpedance, and dual-energy X-ray absorptiometry (DXA), MRI offers direct and precise measurements of the volumes of different tissue compartments and also enables quantification of diffuse fat infiltration in organs. Here, we describe a protocol for acquiring of fat–water-separated MRI data and the image postprocessing required for the quantification of several body composition biomarkers relevant for metabolic research. This protocol has successfully been used in several clinical studies and also in the large UK Biobank population study.
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| 2. |
- Moreno, Rodrigo, 1973-, et al.
(author)
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Anisotropy Estimation of Trabecular Bone in Gray-Scale : Comparison Between Cone Beam and Micro Computed Tomography Data
- 2015
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In: Developments in Medical Image Processing and Computational Vision. - Cham : Springer. - 9783319134062 - 9783319134079 ; , s. 207-220
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Book chapter (peer-reviewed)abstract
- Measurement of anisotropy of trabecular bone has clinical relevance in osteoporosis. In this study, anisotropy measurements of 15 trabecular bone biopsies from the radius estimated by different fabric tensors on images acquired through cone beam computed tomography (CBCT) and micro computed tomography (micro-CT) were compared. The results show that the generalized mean intercept length (MIL) tensor performs better than the global gray-scale structure tensor, especially when the von Mises-Fisher kernel is applied. Also, the generalized MIL tensor yields consistent results between the two scanners. These results suggest that this tensor is appropriate for estimating anisotropy in images acquired in vivo through CBCT.
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| 3. |
- Moreno, Rodrigo, 1973-, et al.
(author)
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Techniques for Computing Fabric Tensors : A Review
- 2014
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In: Visualization and Processing of Tensors and Higher Order Descriptors for Multi-Valued Data. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783642543005 - 9783642543012 ; , s. 271-292
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Book chapter (peer-reviewed)abstract
- The aim of this chapter is to review different approaches that have been proposed to compute fabric tensors with emphasis on trabecular bone research. Fabric tensors aim at modeling through tensors both anisotropy and orientation of a material with respect to another one. Fabric tensors are widely used in fields such as trabecular bone research, mechanics of materials and geology. These tensors can be seen as semi-global measurements since they are computed in relatively large neighborhoods, which are assumed quasi-homogeneous. Many methods have been proposed to compute fabric tensors. We propose to classify fabric tensors into two categories: mechanics-based and morphology-based. The former computes fabric tensors from mechanical simulations, while the latter computes them by analyzing the morphology of the materials. In addition to pointing out advantages and drawbacks for each method, current trends and challenges in this field are also summarized.
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