Готові списки джерел за темами / Applied Physics, Magnetic Resonance Imaging, Magnetic Particle Imaging

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Добірка наукової літератури з теми "Applied Physics, Magnetic Resonance Imaging, Magnetic Particle Imaging"

Автор: Grafiati
Опубліковано: 11 березня 2023

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Статті в журналах з теми "Applied Physics, Magnetic Resonance Imaging, Magnetic Particle Imaging"

1

Herrmann, Anne, Arthur Taylor, Patricia Murray, Harish Poptani, and Violaine Sée. "Magnetic Resonance Imaging for Characterization of a Chick Embryo Model of Cancer Cell Metastases." Molecular Imaging 17 (January 1, 2018): 153601211880958. http://dx.doi.org/10.1177/1536012118809585.

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Анотація:
Metastasis is the most common cause of death for patients with cancer. To fully understand the steps involved in metastatic dissemination, in vivo models are required, of which murine ones are the most common. Therefore, preclinical imaging methods such as magnetic resonance imaging (MRI) have mainly been developed for small mammals and their potential to monitor cancer growth and metastasis in nonmammalian models is not fully harnessed. We have here used MRI to measure primary neuroblastoma tumor size and metastasis in a chick embryo model. We compared its sensitivity and accuracy to end-point fluorescence detection upon dissection. Human neuroblastoma cells labeled with green fluorescent protein (GFP) and micron-sized iron particles were implanted on the extraembryonic chorioallantoic membrane of the chick at E7. T2 RARE, T2-weighted fast low angle shot (FLASH) as well as time-of-flight MR angiography imaging were applied at E14. Micron-sized iron particle labeling of neuroblastoma cells allowed in ovo observation of the primary tumor and tumor volume measurement noninvasively. Moreover, T2 weighted and FLASH imaging permitted the detection of small metastatic deposits in the chick embryo, thereby reinforcing the potential of this convenient, 3R compliant, in vivo model for cancer research.
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2

Baki, Abdulkader, Amani Remmo, Norbert Löwa, Frank Wiekhorst, and Regina Bleul. "Albumin-Coated Single-Core Iron Oxide Nanoparticles for Enhanced Molecular Magnetic Imaging (MRI/MPI)." International Journal of Molecular Sciences 22, no. 12 (June 9, 2021): 6235. http://dx.doi.org/10.3390/ijms22126235.

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Анотація:
Colloidal stability of magnetic iron oxide nanoparticles (MNP) in physiological environments is crucial for their (bio)medical application. MNP are potential contrast agents for different imaging modalities such as magnetic resonance imaging (MRI) and magnetic particle imaging (MPI). Applied as a hybrid method (MRI/MPI), these are valuable tools for molecular imaging. Continuously synthesized and in-situ stabilized single-core MNP were further modified by albumin coating. Synthesizing and coating of MNP were carried out in aqueous media without using any organic solvent in a simple procedure. The additional steric stabilization with the biocompatible protein, namely bovine serum albumin (BSA), led to potential contrast agents suitable for multimodal (MRI/MPI) imaging. The colloidal stability of BSA-coated MNP was investigated in different sodium chloride concentrations (50 to 150 mM) in short- and long-term incubation (from two hours to one week) using physiochemical characterization techniques such as transmission electron microscopy (TEM) for core size and differential centrifugal sedimentation (DCS) for hydrodynamic size. Magnetic characterization such as magnetic particle spectroscopy (MPS) and nuclear magnetic resonance (NMR) measurements confirmed the successful surface modification as well as exceptional colloidal stability of the relatively large single-core MNP. For comparison, two commercially available MNP systems were investigated, MNP-clusters, the former liver contrast agent (Resovist), and single-core MNP (SHP-30) manufactured by thermal decomposition. The tailored core size, colloidal stability in a physiological environment, and magnetic performance of our MNP indicate their ability to be used as molecular magnetic contrast agents for MPI and MRI.
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3

Cenova, Iva, David Kauzlarić, Andreas Greiner, and Jan G. Korvink. "Constrained simulations of flow in haemodynamic devices: towards a computational assistance of magnetic resonance imaging measurements." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 369, no. 1945 (June 28, 2011): 2494–501. http://dx.doi.org/10.1098/rsta.2011.0028.

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Cardiovascular diseases, mostly related to atherosclerosis, are the major cause of death in industrial countries. It is observed that blood flow dynamics play an important role in the aetiology of atherosclerosis. Especially, the blood velocity distribution is an important indicator for predisposition regions. Today magnetic resonance imaging (MRI) delivers, in addition to the morphology of the cardiovascular system, blood flow patterns. However, the spatial resolution of the data is slightly less than 1 mm and owing to severe restrictions in magnetic field gradient switching frequencies and intensities, this limit will be very hard to overcome. In this paper, constrained fluid dynamics is applied within the smoothed particle hydrodynamics formalism to enhance the MRI flow data. On the one hand, constraints based on the known volumetric flow rate are applied. They prove the plausibility of the order of magnitude of the measurements. On the other hand, the higher resolution of the simulation allows one to determine in detail the flow field between the coarse data points and thus to improve their spatial resolution.
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4

TOUFIQ, ARBAB MOHAMMAD, FENGPING WANG, QURAT-UL-AIN JAVED, QUANSHUI LI, and YAN LI. "PHOTOLUMINESCENCE SPECTRA AND MAGNETIC PROPERTIES OF HYDROTHERMALLY SYNTHESIZED MnO2 NANORODS." Modern Physics Letters B 27, no. 29 (November 15, 2013): 1350211. http://dx.doi.org/10.1142/s0217984913502114.

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In this paper, single crystalline tetragonal MnO 2 nanorods have been synthesized by a simple hydrothermal method using MnSO 4⋅ H 2 O and Na 2 S 2 O 8 as precursors. The crystalline phase, morphology, particle sizes and component of the as-prepared nanomaterial were characterized by employing X-ray diffraction (XRD), field-emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HRTEM), selected area electron diffraction (SAED) and energy-dispersive X-ray spectroscopy (EDS). The photoluminescence (PL) emission spectrum of MnO 2 nanorods at room temperature exhibited a strong ultraviolet (UV) emission band at 380 nm, a prominent blue emission peak at 453 nm as well as a weak defect related green emission at 553 nm. Magnetization (M) as a function of applied magnetic field (H) curve showed that MnO 2 nanowires exhibited a superparamagnetic behavior at room temperature which shows the promise of synthesized MnO 2 nanorods for applications in ferrofluids and the contrast agents for magnetic resonance imaging. The magnetization versus temperature curve of the as-obtained MnO 2 nanorods shows that the Néel transition temperature is 94 K.
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5

Ragam, Prashanth, and Devidas Sahebraoji Nimaje. "Evaluation and prediction of blast-induced peak particle velocity using artificial neural network: A case study." Noise & Vibration Worldwide 49, no. 3 (March 2018): 111–19. http://dx.doi.org/10.1177/0957456518763161.

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Over the past few decades, inducing of ground vibrations from blasting may cause severe damage to surrounding structures, plants, and human beings in the mining industry. Therefore, it is essential to monitor and predict the ambiguous vibration levels and take measures to reduce their hazardous effect. In this study, to evaluate and predict the ambiguous ground vibrations, an application of artificial neural network technique was used. A three-layer, feed-forward back-propagation multilayer perception neural network having six input parameters, the distance from blast face, maximum charge per delay, spacing, burden, hole depth and a number of holes, and one output: peak particle velocity, was used and trained with the Levenberg–Marquardt algorithm using 25 experimental and blast event records from the iron ore mine A, India. To determine the efficiency and accuracy of the developed artificial neural network model, seven conventional predictor models proposed by the US Bureau of Mines, Ambraseys–Hendron, Langefors–Kihlstrom, general predictor, Ghosh–Daemen predictor, cardiac magnetic resonance imaging (CMRI) predictor, Bureau of Indian Standards, as well as multiple linear regression, were applied to establish a relation between peak particle velocity and its influencing parameters. The obtained results reveal that the proposed artificial neural network model can estimate ground vibrations more accurately as compared with the various conventional predictor models available. Coefficient of determination (R2) and root mean square error indices were obtained as 0.9971 and 0.08133 for artificial neural network model, respectively.
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6

Korsakova, Alina S., Dzmitry A. Kotsikau, Yulyan S. Haiduk, and Vladimir V. Pankov. "Synthesis and Physicochemical Properties of MnxFe3–xO4 Solid Solutions." Kondensirovannye sredy i mezhfaznye granitsy = Condensed Matter and Interphases 22, no. 4 (December 1, 2020): 466–72. http://dx.doi.org/10.17308/kcmf.2020.22/3076.

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Анотація:
Ferrimagnetic nanoparticles are used in biotechnology (as drug carriers, biosensors, elements of diagnostic sets, contrast agents for magnetic resonance imaging), catalysis, electronics, and for the production of magnetic fluids and magnetorheological suspensions, etc. The use of magnetic nanoparticles requires enhanced magnetic characteristics, in particular, high saturation magnetisation.The aim of our study was to obtain single-phased magnetic nanoparticles of MnxFe3–xO4 solid solutions at room temperature. We also studied the dependence of the changes in their structure, morphology, and magnetic properties on the degree of substitution in order to determine the range of the compounds with the highest magnetisation value.A number of powders of Mn-substituted magnetite MnxFe3–xO4 (x = 0 – 1.8) were synthesized by means of co-precipitation from aqueous solutions of salts. The structural and micro-structural features and magnetic properties of the powders were studied using magnetic analysis, X-ray diffraction, transmission electron microscopy, and IR spectroscopy.The X-ray phase analysis and IR spectroscopy confirm the formation of single-phase compounds with cubic spinel structures. The maximum increase in saturation magnetization as compared to non-substituted magnetite was observed for Mn0.3Fe2.7O4 (Ms = 68 A·m2·kg–1 at 300 K and Ms = 85 A·m2·kg–1 at 5 K). This is associated with the changes in the cation distribution between the tetrahedral and octahedral cites.A method to control the magnetic properties of magnetite by the partial replacement of iron ions in the magnetite structure with manganese has been proposed in the paper. The study demonstrated that it is possible to change the magnetisation and coercivity of powders by changing the degree of substitution. The maximum magnetisation corresponds to the powder Mn0.3Fe2.7O4. The nanoparticles obtained by the proposed method have a comparatively high specific magnetisation and a uniform size distribution. Therefore the developed materials can be used for the production of magnetorheological fluidsand creation of magnetically controlled capsules for targeted drug delivery and disease diagnostics in biology and medicine (magnetic resonance imaging). References1. Gubin C. G., Koksharov Yu. A., Khomutov G. B.,Yurkov G. Yu. Magnetic nanoparticles: preparation,structure and properties. Russian Chemical Reviews2005;74(6): 539–574. Available at: https://www.elibrary.ru/item.asp?id=90858192. Skumr yev V. , Stoyanov S. , Zhang Y. ,Hadjipanayis G., Givord D., Nogués J. Beating thesuperparamagnetic limit with exchange bias. Nature.2003;423(6943): 850–853. DOI: https://doi.org/10.1038/nature016873. Joseph A., Mathew S. Ferrofluids: syntheticstrategies, stabilization, physicochemical features, characterization, and applications. ChemPlusChem.2014;79(10): 1382–1420. DOI: https://doi.org/10.1002/cplu.2014022024. Mathew D. S., Juang R.-S. An overview of thestructure and magnetism of spinel ferrite nanoparticlesand their synthesis in microemulsions. ChemicalEngineering Journal. 2007:129(1–3): 51–65. DOI:https://doi.org/10.1016/j.cej.2006.11.0015. Rewatkar K. G. Magnetic nanoparticles:synthesis and properties. Solid State Phenomena.2016:241: 177–201. DOI: https://doi.org/10.4028/www.scientific.net/ssp.241.1776. Tartaj P., Morales M. P., Veintemillas-VerdaguerS., Gonzalez-Carre´no T., Serna C. J. Thepreparation of magnetic nanoparticles for applicationsin biomedicine. Journal of Physics D: Applied Physics.2003: 36 (13): 182–197. DOI: : https://doi.org/10.1088/0022-3727/36/13/2027. West A. Khimiya tverdogo tela. Teoriya iprilozheniya [Solid State Chemistry and Its Applications].In 2 parts Part 1. Transl. from English. Moscow, Mir,1988 558 p.8. Spravochnik khimika: V 6 t. 2-e izd. Obshchiyesvedeniya. Stroyeniye veshchestva. Svoystva vazhneyshikhveshchestv. Laboratornaya tekhnika [Chemist’sHandbook: In 6 volumes, 2nd ed. General information.The structure of matter. Properties of the mostimportant substances. Laboratory equipment]. B. P.Nikolskiy (ed.) Moscow – Leningrad: GoskhimizdatPubl.; 1963. V. 1. 1071 p. (In Russ.)9. Zhuravlev G. I. Khimiya i tekhnologiya ferritov[Ferrite chemistry and technology]. Leningrad:Khimiya Publ.; 1970. p. 192. (In Russ.)10. Mason B. Mineralogical aspects of the systemFeO-Fe2O3-MnO-Mn2O3. Geologiska Föreningen iStockholm Förhandlingar. 1943;65(2): 97–180. DOI:https://doi.org/10.1080/1103589430944714211. Guillemet-Fritsch S., Navrotsky A., TailhadesPh., Coradin H., Wang M. Thermochemistry of ironmanganese oxide spinels. Journal of Solid StateChemistry. 2005;178(1):106–113. DOI: https://doi.org/10.1016/j.jssc.2004.10.03112. Ortega D. Structure and magnetism in magneticnanoparticles. In: Magnetic Nanoparticles: FromFabrication to Clinical Applications. Boca Raton: CRCPress; 2012. p. 3–72. DOI:https://doi.org/10.1201/b11760-313. Kodama T., Ookubo M., Miura S., Kitayama Y.Synthesis and characterization of ultrafine Mn(II)-bearing ferrite of type MnxFe3-xO4 by coprecipitation.Materials Research Bulletin... 1996:31(12): 1501–1512.DOI: https://doi.org/10.1016/s0025-5408(96)00146-814. Al-Rashdi K. S., Widatallah H., Al Ma’Mari F.,Cespedes O., Elzain M., Al-Rawas A., Gismelseed A.,Yousif A. Structural and mossbauer studies ofnanocrystalline Mn2+ doped Fe3O4 particles. HyperfineInteract. 2018:239(1): 1–11. DOI: https://doi.org/10.1007/s10751-017-1476-915. Modaresi N., Afzalzadeh R., Aslibeiki B.,Kameli P. Competition between the Impact of cationdistribution and crystallite size on properties ofMnxFe3–xO4 nanoparticles synthesized at roomtemperature. Ceramics International. 2017:43(17):15381–15391. DOI: https://doi.org/10.1016/j.ceramint.2017.08.079
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7

Paysen, Hendrik, Norbert Loewa, Karol Weber, Olaf Kosch, James Wells, Tobias Schaeffter, and Frank Wiekhorst. "Imaging and quantification of magnetic nanoparticles: Comparison of magnetic resonance imaging and magnetic particle imaging." Journal of Magnetism and Magnetic Materials 475 (April 2019): 382–88. http://dx.doi.org/10.1016/j.jmmm.2018.10.082.

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8

Wegner, Franz, Kerstin Lüdtke-Buzug, Sjef Cremers, Thomas Friedrich, Malte M. Sieren, Julian Haegele, Martin A. Koch, et al. "Bimodal Interventional Instrument Markers for Magnetic Particle Imaging and Magnetic Resonance Imaging—A Proof-of-Concept Study." Nanomaterials 12, no. 10 (May 21, 2022): 1758. http://dx.doi.org/10.3390/nano12101758.

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The purpose of this work was to develop instrument markers that are visible in both magnetic particle imaging (MPI) and magnetic resonance imaging (MRI). The instrument markers were based on two different magnetic nanoparticle types (synthesized in-house KLB and commercial Bayoxide E8706). Coatings containing one of both particle types were fabricated and measured with a magnetic particle spectrometer (MPS) to estimate their MPI performance. Coatings based on both particle types were then applied on a segment of a nonmetallic guidewire. Imaging experiments were conducted using a commercial, preclinical MPI scanner and a preclinical 1 tesla MRI system. MPI image reconstruction was performed based on system matrices measured with dried KLB and Bayoxide E8706 coatings. The bimodal markers were clearly visible in both methods. They caused circular signal voids in MRI and areas of high signal intensity in MPI. Both the signal voids as well as the areas of high signal intensity were larger than the real marker size. Images that were reconstructed with a Bayoxide E8706 system matrix did not show sufficient MPI signal. Instrument markers with bimodal visibility are essential for the perspective of monitoring cardiovascular interventions with MPI/MRI hybrid systems.
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9

Gladden, Lynn F. "Applications of Nuclear Magnetic Resonance Imaging in Particle Technology." Particle & Particle Systems Characterization 12, no. 2 (April 1995): 59–67. http://dx.doi.org/10.1002/ppsc.19950120203.

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10

Kluth, Tobias. "Mathematical models for magnetic particle imaging." Inverse Problems 34, no. 8 (June 12, 2018): 083001. http://dx.doi.org/10.1088/1361-6420/aac535.

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Дисертації з теми "Applied Physics, Magnetic Resonance Imaging, Magnetic Particle Imaging"

1

Hurdal, Monica Kimberly. "Mathematical and computer modelling of the human brain with reference to cortical magnification and dipole source localisation in the visual cortx." Thesis, Queensland University of Technology, 1998.

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2

Gerosa, Marco. "Tunable iron-based contrast agent for efficient Magnetic Fluid Hyperthermia in Magnetic Resonance Imaging and Magnetic Particle Imaging." Doctoral thesis, 2022. http://hdl.handle.net/11562/1068064.

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In recent years our research group has focused on the study of the biomedical applications of magnetic nanoparticles for therapy and diagnosis (theranostics) of tumor pathologies on animal models. Considering diagnostics, the tomographic and molecular imaging techniques able to detect small quantities of iron (an essential component of magnetic nanoparticles used for biomedical purposes) during in vitro and in vivo experiments were of great interest to the group. For these purposes the techniques mainly used were Nuclear Magnetic Resonance (MRI) and Magnetic Particle Imaging (MPI), able to provide a high morphological tomographic resolution (MRI) and the ability to observe small quantities of iron both in vitro on cells and in vivo on murine models. Considering therapy, magnetic nanoparticles able to produce magnetic hyperthermia were mostly studied. Magnetic hyperthermia is a term used for the generation of heat by nanoparticles once subjected to the application of alternating external magnetic fields. Specifically, one of the main research interests of the group in the last four years was to study, characterize and apply, in breast cancer models (MDA-MB-231 and 4T1) both in vitro and in vivo, nanoparticles with a peculiar magnetic phase transition. These particles have proved able to undergo a magnetic phase transition as a function of the temperature variation, after applying external alternating magnetic fields. In this way it was possible to alter their ability to generate heat. This class of nanoparticles has demonstrated to be an important turning point in the panorama of magnetic hyperthermia in the preclinical field, as they were able to self-regulate the temperature variation produced by the application of external alternating magnetic fields thus preventing the possibility of damaging healthy tissues in the immediate surrounding of the pathological tissues. A wide variety of investigation techniques was adopted to characterize the nanoparticles used for experimental purposes. In particular, techniques such as infrared spectroscopy, X-Ray powder diffraction, dynamic light scattering and transmission electron microscopy have made it possible to understand the physico-chemical nature of the hyperthermia mediators used in the subsequent experimental phase. The application of hyperthermia for in vitro and in vivo experimentation was then observed by means of MRI and MPI investigations subsequently compared with the histological results obtained from the staining of the tissues involved in the studies (typically tumor tissues and the main organs involved in the bioaccumulation of nanoparticles such as the liver, kidneys and spleen). Overall, the in vitro and in vivo results were as relevant as being the subject of a scientific publication and a further future publication currently being finalized, confirming the concrete possibility of their future application in the biomedical clinical field.
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Книги з теми "Applied Physics, Magnetic Resonance Imaging, Magnetic Particle Imaging"

1

Berry, Elizabeth. Fundamentals of MRI: An interactive learning approach. Boca Raton: Taylor & Francis, 2008.

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2

Close, Frank. 8. Applied nuclear physics. Oxford University Press, 2015. http://dx.doi.org/10.1093/actrade/9780198718635.003.0008.

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Nuclear physics is a rich and active field. The large amounts of latent energy within the nuclei of atoms can be liberated in nuclear reactors. Together with nuclear weapons, this is the most familiar application of nuclear physics, but ‘Applied nuclear physics’ provides a summary of other applications to industry, medical science, and human health. The phenomenon of natural radioactivity provides beams of particles, which may be used to initiate other nuclear reactions, or to attack tumours in cancer treatment. Forensics via induced radioactivity, nuclear magnetic resonance imaging (NMRI), and positron emission tomography (PET) scans are also described.
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3

Kundla, E., E. Lippmaa, and T. Saluvere. Magnetic Resonance and Related Phenomena: Proceedings of the XXth Congress AMPERE, Tallinn, August 21-26, 1978. Springer, 2014.

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4

Magnetic Resonance and Related Phenomena: Proceedings of the XXth Congress AMPERE, Tallinn, August 21–26, 1978. Springer, 2013.

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5

Kundla, E., E. Lippmaa, and T. Saluvere. Magnetic Resonance and Related Phenomena: Proceedings of the XXth Congress AMPERE, Tallinn, August 21-26 1978. Springer London, Limited, 2014.

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6

Signal Processing in Magnetic Resonance Spectroscopy with Biomedical Applications. Taylor & Francis, 2010.

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7

A Workbook Approach to the Principles of MRI (Series in Medical Physics and Biomedical Engineering). Taylor & Francis, 2008.

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8

Berry, Elizabeth, and Andrew J. Bulpitt. Fundamentals of MRI: An Interactive Learning Approach. Taylor & Francis Group, 2008.

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9

Berry, Elizabeth, and Andrew J. Bulpitt. Fundamentals of MRI: An Interactive Learning Approach. Taylor & Francis Group, 2008.

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10

Berry, Elizabeth, and Andrew J. Bulpitt. Fundamentals of MRI: An Interactive Learning Approach. Taylor & Francis Group, 2008.

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Частини книг з теми "Applied Physics, Magnetic Resonance Imaging, Magnetic Particle Imaging"

1

Chakraborty, Shouvik, Sankhadeep Chatterjee, Amira S. Ashour, Kalyani Mali, and Nilanjan Dey. "Intelligent Computing in Medical Imaging." In Advancements in Applied Metaheuristic Computing, 143–63. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-4151-6.ch006.

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Biomedical imaging is considered main procedure to acquire valuable physical information about the human body and some other biological species. It produces specialized images of different parts of the biological species for clinical analysis. It assimilates various specialized domains including nuclear medicine, radiological imaging, Positron emission tomography (PET), and microscopy. From the early discovery of X-rays, progress in biomedical imaging continued resulting in highly sophisticated medical imaging modalities, such as magnetic resonance imaging (MRI), ultrasound, Computed Tomography (CT), and lungs monitoring. These biomedical imaging techniques assist physicians for faster and accurate analysis and treatment. The present chapter discussed the impact of intelligent computing methods for biomedical image analysis and healthcare. Different Artificial Intelligence (AI) based automated biomedical image analysis are considered. Different approaches are discussed including the AI ability to resolve various medical imaging problems. It also introduced the popular AI procedures that employed to solve some special problems in medicine. Artificial Neural Network (ANN) and support vector machine (SVM) are active to classify different types of images from various imaging modalities. Different diagnostic analysis, such as mammogram analysis, MRI brain image analysis, CT images, PET images, and bone/retinal analysis using ANN, feed-forward back propagation ANN, probabilistic ANN, and extreme learning machine continuously. Various optimization techniques of ant colony optimization (ACO), genetic algorithm (GA), particle swarm optimization (PSO) and other bio-inspired procedures are also frequently conducted for feature extraction/selection and classification. The advantages and disadvantages of some AI approaches are discussed in the present chapter along with some suggested future research perspectives.
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2

Magee, Patrick, and Mark Tooley. "Imaging and Radiation." In The Physics, Clinical Measurement and Equipment of Anaesthetic Practice for the FRCA. Oxford University Press, 2011. http://dx.doi.org/10.1093/oso/9780199595150.003.0033.

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This chapter explains in simple terms the background physics of imaging using standard X-rays, computed axial tomography (CT), nuclear medicine (including positron emission tomography-PET), and magnetic resonance imaging (MRI). It covers the basics of ionising radiation, and also discusses lasers, which are a form of non-ionising radiation (imaging using ultrasound is covered in Chapter 10). X-rays, CT, aspects of nuclear medicine, and lasers are covered briefly. MRI is examined in more detail as this is a newer modality that is often difficult to comprehend, and in any case often involves the presence of the anaesthetist. Some isotopes are naturally occurring but many of the radioactive nuclides used in medicine are produced artificially by a nuclear reactor or cyclotron. Each of these will provide isotopes that are useful for different purposes. Unstable radioactive nuclides achieve stability by radioactive decay, during which they can lose energy. This occurs in a number of ways. For example, atoms can lose energy by ejection of an alpha particle (an extremely tightly bound basic atomic structure of 2 protons and 2 neutrons, which is equivalent to a helium nucleus). This occurs if they have too many nucleons (protons or neutrons) and results in the atomic number being reduced by two and the atomic mass by 4. Other ways that unstable radionuclides decay include: emission of an electron (β−) from the nucleus if the atoms have an excess of neutrons, or by, either emitting a positron (β+) or capturing an electron if they are neutron deficient. Normally isotopes produced by a reactor will be neutron rich and decay by emitting an electron and the cyclotron will tend to produce isotopes that are proton rich and the decay will then be by emitting a positron. This is illustrated in Table 29.1. The new nuclide formed by the decay process (the daughter nuclide) may be left in an excited nuclear state and can release this excess energy by emission of gamma (γ) radiation as shown in Figure 29.1. This example is where the electron (β−) has been emitted. The situation is more complex when a positron has been emitted.
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3

Khairuzzaman, Abdul Kayom Md, and Saurabh Chaudhury. "Brain MR Image Multilevel Thresholding by Using Particle Swarm Optimization, Otsu Method and Anisotropic Diffusion." In Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention, 1036–51. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-7544-7.ch052.

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Multilevel thresholding is widely used in brain magnetic resonance (MR) image segmentation. In this article, a multilevel thresholding-based brain MR image segmentation technique is proposed. The image is first filtered using anisotropic diffusion. Then multilevel thresholding based on particle swarm optimization (PSO) is performed on the filtered image to get the final segmented image. Otsu function is used to select the thresholds. The proposed technique is compared with standard PSO and bacterial foraging optimization (BFO) based multilevel thresholding techniques. The objective image quality metrics such as Peak Signal to Noise Ratio (PSNR) and Mean Structural SIMilarity (MSSIM) index are used to evaluate the quality of the segmented images. The experimental results suggest that the proposed technique gives significantly better-quality image segmentation compared to the other techniques when applied to T2-weitghted brain MR images.
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Zouaoui, Hakima, and Abdelouahab Moussaoui. "Bioinspired Inference System for MR Image Segmentation and Multiple Sclerosis Detection." In Research Anthology on Improving Medical Imaging Techniques for Analysis and Intervention, 649–70. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-7544-7.ch032.

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Multiple sclerosis (MS) is a chronic autoimmune and inflammatory disease affecting the central nervous system (CNS). Magnetic resonance imaging (MRI) provides sufficient imaging contrast to visualize and detect MS lesions, particularly those in the white matter (WM). A robust and precise segmentation of WM lesions from MRI provide essential information about the disease status and evolution. The proposed FPSOPCM segmentation algorithm included an initial segmentation step using fuzzy particle swarm optimization (FPSO). After extraction of WM, atypical data (outliers) is eliminated using possibilistic C-means (PCM) algorithm, and finally, a Mamdani-type fuzzy model was applied to identify MS. The objective of the work presented in this paper is to obtain an improved accuracy in segmentation of MR images for MS detection.
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Dey, Nilanjan, and Amira S. Ashour. "Meta-Heuristic Algorithms in Medical Image Segmentation." In Advancements in Applied Metaheuristic Computing, 185–203. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-4151-6.ch008.

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Artificial intelligence is the outlet of computer science apprehensive with creating computers that perform as humans. It compromises expert systems, playing games, natural language, and robotics. However, soft computing (SC) varies from the hard (conventional) computing in its tolerant of partial truth, uncertainty, imprecision, and approximation, thus, it models the human mind. The most common SC techniques include neural networks, fuzzy systems, machine learning, and the meta-heuristic stochastic algorithms (e.g., Cellular automata, ant colony optimization, Memetic algorithms, particle swarms, Tabu search, evolutionary computation and simulated annealing. Due to the required accurate diseases analysis, magnetic resonance imaging, computed tomography images and images of other modalities segmentation remains a challenging problem. Over the past years, soft computing approaches attract attention of several researchers for problems solving in medical data applications. Image segmentation is the process that partitioned an image into some groups based on similarity measures. This process is employed for abnormalities volumetric analysis in medical images to identify the disease nature. Recently, meta-heuristic algorithms are conducted to support the segmentation techniques. In the current chapter, different segmentation procedures are addressed. Several meta-heuristic approaches are reported with highlights on their procedures. Finally, several medical applications using meta-heuristic based-approaches for segmentation are discussed.
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Marks II, Robert J. "Introduction." In Handbook of Fourier Analysis & Its Applications. Oxford University Press, 2009. http://dx.doi.org/10.1093/oso/9780195335927.003.0006.

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Jean Baptiste Joseph Fourier’s powerful idea of decomposition of a signal into sinusoidal components has found application in almost every engineering and science field. An incomplete list includes acoustics [1497], array imaging [1304], audio [1290], biology [826], biomedical engineering [1109], chemistry [438, 925], chromatography [1481], communications engineering [968], control theory [764], crystallography [316, 498, 499, 716], electromagnetics [250], imaging [151], image processing [1239] including segmentation [1448], nuclear magnetic resonance (NMR) [436, 1009], optics [492, 514, 517, 1344], polymer characterization [647], physics [262], radar [154, 1510], remote sensing [84], signal processing [41, 154], structural analysis [384], spectroscopy [84, 267, 724, 1220, 1293, 1481, 1496], time series [124], velocity measurement [1448], tomography [93, 1241, 1242, 1327, 1330, 1325, 1331], weather analysis [456], and X-ray diffraction [1378], Jean Baptiste Joseph Fourier’s last name has become an adjective in the terms like Fourier series [395], Fourier transform [41, 51, 149, 154, 160, 437, 447, 926, 968, 1009, 1496], Fourier analysis [151, 379, 606, 796, 1472, 1591], Fourier theory [1485], the Fourier integral [395, 187, 1399], Fourier inversion [1325], Fourier descriptors [826], Fourier coefficients [134], Fourier spectra [624, 625] Fourier reconstruction [1330], Fourier spectrometry [84, 355], Fourier spectroscopy [1220, 1293, 1438], Fourier array imaging [1304], Fourier transform nuclear magnetic resonance (NMR) [429, 1004], Fourier vision [1448], Fourier optics [419, 517, 1343], and Fourier acoustics [1496]. Applied Fourier analysis is ubiquitous simply because of the utility of its descriptive power. It is second only to the differential equation in the modelling of physical phenomena. In contrast with other linear transforms, the Fourier transform has a number of physical manifestations. Here is a short list of everyday occurrences as seen through the lens of the Fourier paradigm. • Diffracting coherent waves in sonar and optics in the far field are given by the two dimensional Fourier transform of the diffracting aperture. Remarkably, in free space, the physics of spreading light naturally forms a two dimensional Fourier transform. • The sampling theorem, born of Fourier analysis, tells us how fast to sample an audio waveform to make a discrete time CD or an image to make a DVD.
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Тези доповідей конференцій з теми "Applied Physics, Magnetic Resonance Imaging, Magnetic Particle Imaging"

1

Salim, Safyzan, Muhammad Mahadi Abdul Jamil, Abdulkadir Abubakar Sadiq, Noordin Asimi Mohd Noor, Nur Adilah Abd Rahman, and Nurmiza Othman. "Single-sided magnetic particle imaging using perimag magnetic nanoparticles." In APPLIED PHYSICS OF CONDENSED MATTER (APCOM 2019). AIP Publishing, 2019. http://dx.doi.org/10.1063/1.5118127.

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Amador, R. "Magnetic Resonance Imaging Applied to Biomedical Porous Media." In MEDICAL PHYSICS: Seventh Mexican Symposium on Medical Physics. AIP, 2003. http://dx.doi.org/10.1063/1.1615112.

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Schibli, Matthias, Markus Wiesendanger, Lino Guzzella, Klaus Hoyer, Michaela Soellinger, Vartan Kurtcuoglu, and Peter Boesiger. "In-vitro measurement of ventricular cerebrospinal fluid flow using particle tracking velocimetry and magnetic resonance imaging." In 2008 First International Symposium on Applied Sciences on Biomedical and Communication Technologies (ISABEL). IEEE, 2008. http://dx.doi.org/10.1109/isabel.2008.4712622.

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George, D. L., S. L. Ceccio, T. J. O’Hern, K. A. Shollenberger, and J. R. Torczynski. "Advanced Material Distribution Measurement in Multiphase Flows: A Case Study." In ASME 1998 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/imece1998-0984.

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Abstract A variety of tomographic techniques that have been applied to multiphase flows are described. The methods discussed include electrical impedance tomography (EIT), magnetic resonance imaging (MRI), positron emission tomography (PET), gamma-densitometry tomography (GDT), radiative particle tracking (RDT), X-ray imaging, and acoustic tomography. Also presented is a case study in which measurements were made with EIT and GDT in two-phase flows. Both solid-liquid and gas-liquid flows were examined. EIT and GDT were applied independently to predict mean and spatially resolved phase volume fractions. The results from the two systems compared well.
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