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Relevant bibliographies by topics / Water/fat imaging

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Dissertations / Theses

Academic literature on the topic 'Water/fat imaging'

Author: Grafiati

Published: 19 April 2023

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Dissertations / Theses on the topic "Water/fat imaging"

1

An, Li. "Water-fat imaging and general chemical shift imaging with spectrum modeling." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape9/PQDD_0032/NQ38848.pdf.

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2

Huang, Fangping. "Water and Fat Image Reconstruction in Magnetic Resonance Imaging." Case Western Reserve University School of Graduate Studies / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=case1309791802.

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3

Mehemed, Taha Mohamed M. "Fat-Water Interface on Susceptibility-Weighted Imaging and Gradient-Echo Imaging: Comparison of Phantoms to Intracranial Lipomas." Kyoto University, 2014. http://hdl.handle.net/2433/193572.

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4

Berglund, Johan. "Separation of Water and Fat Signal in Magnetic Resonance Imaging : Advances in Methods Based on Chemical Shift." Doctoral thesis, Uppsala universitet, Enheten för radiologi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-158111.

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Magnetic resonance imaging (MRI) is one of the most important diagnostic tools of modern healthcare. The signal in medical MRI predominantly originates from water and fat molecules. Separation of the two components into water-only and fat-only images can improve diagnosis, and is the premier non-invasive method for measuring the amount and distribution of fatty tissue. Fat-water imaging (FWI) enables fast fat/water separation by model-based estimation from chemical shift encoded data, such as multi-echo acquisitions. Qualitative FWI is sufficient for visual separation of the components, while

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5

Sun, Ling. "3D Mellisa : a new three dimensional fat/water image acquisition technique for magnetic resonance imaging /." The Ohio State University, 1994. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487854314873059.

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6

Shibahara, Eriko, Hiroshi Fukatsu, Shinji Naganawa, et al. "Water fat separation using the single acquisition "sandwich" type 3-point Dixon method to optimize knee joint scans." Nagoya University School of Medicine, 2000. http://hdl.handle.net/2237/5354.

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7

Bookwalter, Candice Anne. "CONTINUOUS SAMPLING IN MAGNETIC RESONANCE IMAGING." Case Western Reserve University School of Graduate Studies / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=case1194049081.

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8

Mendoza, Michael A. "Water Fat Separation with Multiple-Acquisition Balanced Steady-State Free Precession MRI." BYU ScholarsArchive, 2013. https://scholarsarchive.byu.edu/etd/4304.

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Magnetic resonance imaging (MRI) is an important medical imaging technique for visualizing soft tissue structures in the body. It has the advantages of being noninvasive and, unlike x-ray, does not rely on ionizing radiation for imaging. In traditional hydrogen-based MRI, the strongest measured signals are generated from the hydrogen nuclei contained in water and fat molecules.Reliable and uniform water fat separation can be used to improve medical diagnosis. In many applications the water component is the primary signal of interest, while the fat component represents a signal which can obscur

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9

Salvati, Roberto. "Development of Magnetic Resonance Imaging (MRI) methods for in vivo quantification of lipids in preclinical models." Thesis, Rennes 1, 2015. http://www.theses.fr/2015REN1B026/document.

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L'obésité est associée à une augmentation de la morbidité et de la mortalité liée à de nombreuses maladies, y compris le diabète de type 2, l'hypertension et des pathologies hépatiques menant à une surcharge lipidique d’origine non alcoolique. Récemment, l’imagerie par résonance magnétique (IRM) est devenue la méthode de choix pour la quantification non invasive de la graisse. Dans cette thèse, les méthodes d'IRM ont été étudiées sur un scanner préclinique de 4.7T in vitro (fantômes MR) et in vivo (souris). Deux algorithmes de quantifications de la graisse -la méthode de Dixon et l’algorithme

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10

Belbaisi, Adham. "Deep Learning-Based Skeleton Segmentation for Analysis of Bone Marrow and Cortical Bone in Water-Fat Magnetic Resonance Imaging." Thesis, KTH, Skolan för kemi, bioteknologi och hälsa (CBH), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-297528.

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A major health concern for subjects with diabetes is weaker bones and increased fracture risk. Current clinical assessment of the bone strength is performed by measuring Bone Mineral Density (BMD), where low BMD-values are associated with an increased risk of fracture. However, subjects with Type 2 Diabetes (T2D) have been shown to have normal or higher BMD-levels compared to healthy controls, which does not reflect the recognized bone fragility among diabetics. Thus, there is need for more research about diabetes-related bone fragility to find other factors of impaired bone health. One potent

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