Fully automatic and nonparametric quantification of adipose tissue in fat–water separation MR imaging
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Brian Tomlinson | Defeng Wang | Lin Shi | Pheng-Ann Heng | Tianfu Wang | Miao Hu | David Ka Wai Yeung | Winnie C. W. Chu | Anil T. Ahuja | Wen-Hua Huang | P. Heng | Lin Shi | W. Chu | Defeng Wang | D. Yeung | A. Ahuja | Tianfu Wang | B. Tomlinson | Wen-Hua Huang | Miao Hu
[1] Alistair A. Young,et al. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , 2017, MICCAI 2017.
[2] Kostas Delibasis,et al. A novel tool for segmenting 3D medical images based on generalized cylinders and active surfaces , 2013, Comput. Methods Programs Biomed..
[3] Bernd Freisleben,et al. Segmentation of pituitary adenoma: A graph-based method vs. a balloon inflation method , 2013, Comput. Methods Programs Biomed..
[4] Cecilia Sjöberg,et al. Multi-atlas based segmentation using probabilistic label fusion with adaptive weighting of image similarity measures , 2013, Comput. Methods Programs Biomed..
[5] M. R. Cheung,et al. Using manual prostate contours to enhance deformable registration of endorectal MRI , 2012, Comput. Methods Programs Biomed..
[6] Meritxell Bach Cuadra,et al. A review of atlas-based segmentation for magnetic resonance brain images , 2011, Comput. Methods Programs Biomed..
[7] H. Eggers,et al. Dual‐echo Dixon imaging with flexible choice of echo times , 2011, Magnetic resonance in medicine.
[8] Rasmus Larsen,et al. Unsupervised Assessment of Subcutaneous and Visceral Fat by MRI , 2009, SCIA.
[9] Örjan Smedby,et al. Quantification of abdominal fat accumulation during hyperalimentation using MRI , 2009 .
[10] Örjan Smedby,et al. Quantitative abdominal fat estimation using MRI , 2008, 2008 19th International Conference on Pattern Recognition.
[11] A. Horská,et al. Quantitative comparison and evaluation of software packages for assessment of abdominal adipose tissue distribution by magnetic resonance imaging , 2008, International Journal of Obesity.
[12] C. McKenzie,et al. Validation of Fat Volume Quantification with IDEAL MRI , 2008 .
[13] Qi Peng,et al. Automated method for accurate abdominal fat quantification on water‐saturated magnetic resonance images , 2007, Journal of magnetic resonance imaging : JMRI.
[14] J. Kullberg,et al. Automated and reproducible segmentation of visceral and subcutaneous adipose tissue from abdominal MRI , 2007, International Journal of Obesity.
[15] R. Semelka,et al. Accurate quantification of visceral adipose tissue (VAT) using water‐saturation MRI and computer segmentation: Preliminary results , 2006, Journal of magnetic resonance imaging : JMRI.
[16] W. Chan,et al. The preferred magnetic resonance imaging planes in quantifying visceral adipose tissue and evaluating cardiovascular risk , 2005, Diabetes, obesity & metabolism.
[17] Luigi Landini,et al. An accurate and robust method for unsupervised assessment of abdominal fat by MRI , 2004, Journal of magnetic resonance imaging : JMRI.
[18] W. Chan,et al. Sonographic measurement of mesenteric fat thickness is a good correlate with cardiovascular risk factors: comparison with subcutaneous and preperitoneal fat thickness, magnetic resonance imaging and anthropometric indexes , 2003, International Journal of Obesity.
[19] Lutz Heinemann,et al. A rapid and reliable semiautomated method for measurement of total abdominal fat volumes using magnetic resonance imaging. , 2003, Magnetic resonance imaging.
[20] J. Després,et al. Waist circumference, visceral obesity, and cardiovascular risk. , 2003, Journal of cardiopulmonary rehabilitation.
[21] Masafumi Matsuda,et al. Metabolic effects of visceral fat accumulation in type 2 diabetes. , 2002, The Journal of clinical endocrinology and metabolism.
[22] M. Shinomiya,et al. A novel method of measuring intra-abdominal fat volume using helical computed tomography , 2002, International Journal of Obesity.
[23] B. Wajchenberg. Subcutaneous and visceral adipose tissue: their relation to the metabolic syndrome. , 2000, Endocrine reviews.
[24] P. Kopelman. Obesity as a medical problem , 2000, Nature.
[25] P. Tothill,et al. Measurement of abdominal fat by magnetic resonance imaging, dual-energy X-ray absorptiometry and anthropometry in non-obese men and women , 1999, International Journal of Obesity.
[26] Alan C. Evans,et al. A nonparametric method for automatic correction of intensity nonuniformity in MRI data , 1998, IEEE Transactions on Medical Imaging.
[27] R M Peshock,et al. Estimation of adipose tissue mass by magnetic resonance imaging: validation against dissection in human cadavers. , 1994, Journal of lipid research.
[28] J. Seidell,et al. Techniques for the measurement of visceral fat: a practical guide. , 1993, International journal of obesity and related metabolic disorders : journal of the International Association for the Study of Obesity.
[29] Enzo Bonora,et al. Measurement of abdominal fat with T1‐weighted MR images , 1991, Journal of magnetic resonance imaging : JMRI.
[30] J H Ruijs,et al. Assessment of intra-abdominal and subcutaneous abdominal fat: relation between anthropometry and computed tomography. , 1987, The American journal of clinical nutrition.
[31] John F. Canny,et al. A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[32] D. Altman,et al. STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT , 1986, The Lancet.
[33] S. P. Lloyd,et al. Least squares quantization in PCM , 1982, IEEE Trans. Inf. Theory.
[34] A. Beckett,et al. AKUFO AND IBARAPA. , 1965, Lancet.
[35] Junaed Sattar. Snakes , Shapes and Gradient Vector Flow , 2022 .