[1] J. Seymour et al., "The prevalence of quadriceps weakness in COPD and the relationship with disease severity," European Respiratory Journal, vol. 36, no. 1, pp. 81-88, 2010.
[2] M. M. McDermott et al., "Pathophysiological changes in calf muscle predict mobility loss at 2-year follow-up in men and women with peripheral arterial disease," Circulation, vol. 120, no. 12, pp. 1048-1055, 2009.
[3] A. E. Emery, "The muscular dystrophies," The Lancet, vol. 359, no. 9307, pp. 687-695, 2002.
[4] K. Uemura, M. Takao, T. Sakai, T. Nishii, and N. Sugano, "Volume increases of the gluteus maximus, gluteus medius, and thigh muscles after hip arthroplasty," The Journal of arthroplasty, vol. 31, no. 4, pp. 906-912. e1, 2016.
[5] S. Orgiu, C. L. Lafortuna, F. Rastelli, M. Cadioli, A. Falini, and G. Rizzo, "Automatic muscle and fat segmentation in the thigh from T1‐Weighted MRI," Journal of Magnetic Resonance Imaging, vol. 43, no. 3, pp. 601-610, 2016.
[6] C. Tan et al., "An automated and robust framework for quantification of muscle and fat in the thigh," in Pattern Recognition (ICPR), 2014 22nd International Conference on, 2014, pp. 3173-3178: IEEE.
[7] E. Ahmad, M. H. Yap, H. Degens, and J. S. McPhee, "Atlas-registration based image segmentation of MRI human thigh muscles in 3D space," in Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment, 2014, vol. 9037, p. 90371L: International Society for Optics and Photonics.
[8] A. Karlsson et al., "Automatic and quantitative assessment of regional muscle volume by multi‐atlas segmentation using whole‐body water–fat MRI," Journal of Magnetic Resonance Imaging, vol. 41, no. 6, pp. 1558-1569, 2015.
[9] F. Yokota, "Automated muscle segmentation from 3D CT data of the hip using a hierarchical multi-atlas method," in 12th annual meeting of CAOS-international proceedings, 2012, pp. 30-32.
[10]F. Yokota et al., "Automated muscle segmentation from CT images of the hip and thigh using a hierarchical multi-atlas method," International journal of computer assisted radiology and surgery, pp. 1-10, 2018.
[11]S. Andrews and G. Hamarneh, "The generalized log-ratio transformation: learning shape and adjacency priors for simultaneous thigh muscle segmentation," IEEE transactions on medical imaging, vol. 34, no. 9, pp. 1773-1787, 2015.
[12]S. Andrews, G. Hamarneh, A. Yazdanpanah, B. HajGhanbari, and W. D. Reid, "Probabilistic multi-shape segmentation of knee extensor and flexor muscles," in International Conference on Medical Image Computing and Computer-Assisted Intervention, 2011, pp. 651-658: Springer.
[13]E. Jolivet et al., "Skeletal muscle segmentation from MRI dataset using a model-based approach," Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization 2, no. 3, pp. 138-145, 2014.
[14]P.-Y. Baudin, N. Azzabou, P. G. Carlier, and N. Paragios, "Automatic skeletal muscle segmentation through random walks and graph-based seed placement," in Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on, 2012, pp. 1036-1039: IEEE.
[15]P.-Y. Baudin, N. Azzabou, P. G. Carlier, and N. Paragios, "Prior knowledge, random walks and human skeletal muscle segmentation," In International Conference on Medical Image Computing and Computer-assisted Intervention, pp. 569-576. Springer, Berlin, Heidelberg, 2012.
[16]A. Le Troter et al., "Volume measurements of individual muscles in human quadriceps femoris using atlas-based segmentation approaches," Magnetic Resonance Materials in Physics, Biology and Medicine, vol. 29, no. 2, pp. 245-257, 2016.
[17]J. Kemnitz et al., "Validation of an active shape model-based semi-automated segmentation algorithm for the analysis of thigh muscle and adipose tissue cross-sectional areas," Magnetic Resonance Materials in Physics, Biology and Medicine, vol. 30, no. 5, pp. 489-503, 2017.
[18]J. Kemnitz et al., "Validation of a 3D thigh muscle and adipose tissue segmentation method using statistical shape models," Osteoarthritis and Cartilage, vol. 26, pp. S457-S458, 2018.
[19]J. W. Prescott, T. M. Best, M. S. Swanson, F. Haq, R. D. Jackson, and M. N. Gurcan, "Anatomically anchored template-based level set segmentation: application to quadriceps muscles in MR images from the Osteoarthritis Initiative," Journal of digital imaging, vol. 24, no. 1, pp. 28-43, 2011.
[20]E. Blaak, "Gender differences in fat metabolism," Current Opinion in Clinical Nutrition & Metabolic Care, vol. 4, no. 6, pp. 499-502, 2001.
[21]M. Kistler, S. Bonaretti, M. Pfahrer, R. Niklaus, and P. Büchler, "The virtual skeleton database: an open access repository for biomedical research and collaboration," Journal of medical Internet research, vol. 15, no. 11, p. e245, 2013.
[22]K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, "Joint image sharpening and denoising by 3D transform-domain collaborative filtering," in Proc. 2007 Int. TICSP Workshop Spectral Meth. Multirate Signal Process., SMMSP, 2007, vol. 2007.
[23]C. Pérez-Benito, S. Morillas, C. Jordán, and J. A. Conejero, "Smoothing vs. sharpening of colour images: Together or separated," Applied Mathematics and Nonlinear Sciences, vol. 2, no. 1, pp. 299-316, 2017.
[24]V. Katkovnik, A. Foi, and K. Egiazarian, "Advanced Image Processing Based on Spatially Adaptive Nonlocal Image Filtering and Regularization," In Image Processing (ICIP), 2010 17th IEEE International Conference on (pp. 1-296)..
[25]Y. Hou, "Nonlocal Estimation and BM3D Based Face Illumination Normalization," in International Conference on Intelligent and Interactive Systems and Applications, 2018, pp. 115-122: Springer.
[26]J. C. Bezdek, R. Ehrlich, and W. Full, "FCM: The fuzzy c-means clustering algorithm," Computers & Geosciences, vol. 10, no. 2-3, pp. 191-203, 1984.
[27]I. Isgum, M. Staring, A. Rutten, M. Prokop, M. A. Viergever, and B. Van Ginneken, "Multi-atlas-based segmentation with local decision fusion—application to cardiac and aortic segmentation in CT scans," IEEE transactions on medical imaging, vol. 28, no. 7, pp. 1000-1010, 2009.
[28]T. Lei, X. Jia, Y. Zhang, L. He, H. Meng, and A. K. Nandi, "Significantly fast and robust fuzzy c-means clustering algorithm based on morphological reconstruction and membership filtering," IEEE Transactions on Fuzzy Systems, 2018.
[29]B. Glocker, A. Sotiras, N. Komodakis, and N. Paragios, "Deformable medical image registration: setting the state of the art with discrete methods," Annual review of biomedical engineering, vol. 13, pp. 219-244, 2011.
[30]Taha and A. Hanbury, "Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool," BMC medical imaging, vol. 15, no. 1, p. 29, 2015.