Relevant bibliographies by topics / MRI methods

Academic literature on the topic 'MRI methods'

Author: Grafiati
Published: 8 June 2024

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Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Journal articles on the topic "MRI methods":

1

Kozaitis, Samuel. "Denoising Methods for MRI Imagery." American Journal of Engineering and Applied Sciences 10, no. 3 (March 1, 2017): 655–60. http://dx.doi.org/10.3844/ajeassp.2017.655.660.

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Piccolomini, E. Loli, F. Zama, G. Zanghirati, and A. Formiconi. "Regularization methods in dynamic MRI." Applied Mathematics and Computation 132, no. 2-3 (November 2002): 325–39. http://dx.doi.org/10.1016/s0096-3003(01)00196-5.

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Madelin, Guillaume, Jae-Seung Lee, Ravinder R. Regatte, and Alexej Jerschow. "Sodium MRI: Methods and applications." Progress in Nuclear Magnetic Resonance Spectroscopy 79 (May 2014): 14–47. http://dx.doi.org/10.1016/j.pnmrs.2014.02.001.

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Madhuranthakam, Ananth J., Qing Yuan, and Ivan Pedrosa. "Quantitative Methods in Abdominal MRI." Topics in Magnetic Resonance Imaging 26, no. 6 (December 2017): 251–58. http://dx.doi.org/10.1097/rmr.0000000000000145.

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Clarke, L. P., R. P. Velthuizen, M. A. Camacho, J. J. Heine, M. Vaidyanathan, L. O. Hall, R. W. Thatcher, and M. L. Silbiger. "MRI segmentation: Methods and applications." Magnetic Resonance Imaging 13, no. 3 (January 1995): 343–68. http://dx.doi.org/10.1016/0730-725x(94)00124-l.

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Bogachev, Yu V., A. V. Nikitina, and M. N. Shishkina. "Advanced Methods of Magnetic Resonance Theranostics." LETI Transactions on Electrical Engineering & Computer Science 16, no. 1 (2023): 5–24. http://dx.doi.org/10.32603/2071-8985-2023-16-1-5-24.

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The combination of high-resolution and high-sensitivity diagnostic methods with the therapy of socially significant diseases under the influence of various physical fields, methods or substances is the basis of new intensively developed areas of modern medicine. This review article analyzes advanced methods of magnetic resonance (MR) theranostics, such as MRI-guided laser therapy, MRI tracking in stem cell therapy, MRguided therapy using MRI-theranostic agents based on magnetic nanoparticles, transcranial magnetic stimulation combined with functional MRI (TMS/fMRI). The paper presents both research materials and examples of clinical applications of these methods.
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Sijens, P. E. "Combining New MRI Methods - MR Spectroscopy, Functional MRI, Diffusion Tensor Imaging." Imaging Decisions MRI 9, no. 1 (April 2005): 39–48. http://dx.doi.org/10.1111/j.1617-0830.2005.00039.x.

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Miller, Karla L., Rob HN Tijssen, Nikola Stikov, and Thomas W. Okell. "Steady-state MRI: methods for neuroimaging." Imaging in Medicine 3, no. 1 (February 2011): 93–105. http://dx.doi.org/10.2217/iim.10.66.

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Kanwal, Laraib, and Usman Shahid. "A Review on MRI Denoising Methods." Lahore Garrison University Journal of Life Sciences 3, no. 3 (April 22, 2020): 132–39. http://dx.doi.org/10.54692/lgujls.2019.030369.

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Many years ago, a lot of work has been done to enhance the resolution and signal-to-noise ratio of magnetic resonance images for accurate monitoring. However, artifacts and random noise still affects the quality of Magnetic Resonance images. In order to maintain the relevant image content, compensation between noise reduction and preservation of details have to be made. Therefore, noise reduction is a paramount challenge. A published literature review of each technique is discussed along with its advantages and limitations. After the introduction of magnetic resonance imaging (MRI) technology, the famous approaches for denoising MRI images are classified with overview of each method.
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Borrero, Camilo G., James M. Mountz, and John D. Mountz. "Emerging MRI methods in rheumatoid arthritis." Nature Reviews Rheumatology 7, no. 2 (November 2, 2010): 85–95. http://dx.doi.org/10.1038/nrrheum.2010.173.

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Journal articles Dissertations / Theses Books

Dissertations / Theses on the topic "MRI methods":

1

Mougin, Olivier. "Quantitative methods in high field MRI." Thesis, University of Nottingham, 2010. http://eprints.nottingham.ac.uk/11608/.

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The increased signal-to-noise ratio available at high magnetic field makes possible the acquisition of clinically useful MR images either at higher resolution or for quantitative methods. The work in this thesis is focused on the development of quantitative imaging methods used to overcome difficulties due to high field MRI systems (> 3T). The protocols developed and presented here have been tested on various studies aiming at discriminating tissues based on their NMR properties. The quantities of interest in this thesis are the longitudinal relaxation time T1, as well as the magnetization transfer process, particularly the chemical exchange phenomenon involving amide protons which is highlighted particularly well at 7T under specific conditions. Both quantities (T1 and amide proton transfer) are related to the underlying structure of the tissues in-vivo, especially inside the white matter of the brain. While a standard weighted image at high resolution can provide indices of the extent of the pathology, a robust measure of the NMR properties of brain tissues can detect earlier abnormalities. A method based on a 3D Turbo FLASH readout and measuring reliably the T1 in-vivo for clinical studies at 7T is first presented. The other major part of this thesis presents magnetization transfer and chemical exchange phenomena. First a quantitative method is investigated at 7T, leading to a new model for exchange as well as contrast optimization possibility for imaging. Results using those methods are presented and applied in clinical setting, the main focus being to image reliably the brain of both healthy subjects and Multiple Sclerosis patients to look at myelin structures.
2

Morra, Jonathan Harold. "Learning methods for brain MRI segmentation." Diss., Restricted to subscribing institutions, 2009. http://proquest.umi.com/pqdweb?did=1905693471&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Groves, Adrian R. "Bayesian learning methods for modelling functional MRI." Thesis, University of Oxford, 2009. http://ora.ox.ac.uk/objects/uuid:fe46e696-a1a6-4a9d-9dfe-861b05b1ed33.

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Bayesian learning methods are the basis of many powerful analysis techniques in neuroimaging, permitting probabilistic inference on hierarchical, generative models of data. This thesis primarily develops Bayesian analysis techniques for magnetic resonance imaging (MRI), which is a noninvasive neuroimaging tool for probing function, perfusion, and structure in the human brain. The first part of this work fits nonlinear biophysical models to multimodal functional MRI data within a variational Bayes framework. Simultaneously-acquired multimodal data contains mixtures of different signals and therefore may have common noise sources, and a method for automatically modelling this correlation is developed. A Gaussian process prior is also used to allow spatial regularization while simultaneously applying informative priors on model parameters, restricting biophysically-interpretable parameters to reasonable values. The second part introduces a novel data fusion framework for multivariate data analysis which finds a joint decomposition of data across several modalities using a shared loading matrix. Each modality has its own generative model, including separate spatial maps, noise models and sparsity priors. This flexible approach can perform supervised learning by using target variables as a modality. By inferring the data decomposition and multivariate decoding simultaneously, the decoding targets indirectly influence the component shapes and help to preserve useful components. The same framework is used for unsupervised learning by placing independent component analysis (ICA) priors on the spatial maps. Linked ICA is a novel approach developed to jointly decompose multimodal data, and is applied to combined structural and diffusion images across groups of subjects. This allows some of the benefits of tensor ICA and spatially-concatenated ICA to be combined, and allows model comparison between different configurations. This joint decomposition framework is particularly flexible because of its separate generative models for each modality and could potentially improve modelling of functional MRI, magnetoencephalography, and other functional neuroimaging modalities.
4

Ivarsson, Magnus. "Evaluation of 3D MRI Image Registration Methods." Thesis, Linköpings universitet, Datorseende, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-139075.

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Image registration is the process of geometrically deforming a template image into a reference image. This technique is important and widely used within thefield of medical IT. The purpose could be to detect image variations, pathologicaldevelopment or in the company AMRA’s case, to quantify fat tissue in variousparts of the human body.From an MRI (Magnetic Resonance Imaging) scan, a water and fat tissue image isobtained. Currently, AMRA is using the Morphon algorithm to register and segment the water image in order to quantify fat and muscle tissue. During the firstpart of this master thesis, two alternative registration methods were evaluated.The first algorithm was Free Form Deformation which is a non-linear parametricbased method. The second algorithm was a non-parametric optical flow basedmethod known as the Demon algorithm. During the second part of the thesis,the Demon algorithm was used to evaluate the effect of using the fat images forregistrations.
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Malik, Shaihan. "Data Driven Reconstruction Methods for Dynamic Undersampled MRI." Thesis, Imperial College London, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.486758.

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Dynamic undersampling of MRI data can be used in order to accelerate image acquisition by exploiting the inherent information redundancy existing in sequences of dynamic images. Regions within the field of view (FOV) are forced to share temporal bandwidth, this leads to more efficient encoding so long as regions requiring a large bandwidth are not forced to share. It is noted that existing image reconstruction techniques (for example k-t SENSE) can cause temporal blurring whilst attempting to filter noise from reconstructed images. A new reconstruction technique named x-f choice is proposed, with the aim of reducing this effect. Image reconstruction techniques for dynamic undersampled data in general require some estimate of the expected temporal variation. Existing methods use low resolution images as a pragmatic solution, it is shown that errors can result from this. In this project methods for extracting this information from undersampled data have been investigated. The focus has been on identifying temporally correlated signals within the undersampled data, so that information lost by undersampling may be estimated from elsewhere without the need for extra data. X-f choice in conjunction with analysis of temporal correlations has been used to successfully reconstructed DCE-MRA data acquired in vivo without the need for any extra information at reduction factors of up to 9. It is shown that temporal correlations may be used in order to improve image reconstruction quality in a variety of cases including cardiac imaging, using both x-f choice and the existing reconstruction technique k-t SENSE.
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Niazy, Rami. "Simultaneous electroencephalography and functional MRI : methods and applications." Thesis, University of Oxford, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.483692.

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Rababa`h, Qasim. "Perfusion MRI of gliomas - comparison of analysis methods." Thesis, Örebro universitet, Institutionen för hälsovetenskap och medicin, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-37302.

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Pietsch, Maximilian Rainer. "Advanced diffusion MRI analysis methods for neonatal imaging." Thesis, King's College London (University of London), 2018. https://kclpure.kcl.ac.uk/portal/en/theses/advanced-diffusion-mri-analysis-methods-for-neonatal-imaging(3d1a8dc2-070c-4651-9a42-5171d6ebbab1).html.

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Developmental processes taking place during the third trimester and the neonatal period lay the foundation for a functioning human brain. In the course of these months, neuronal migration, cellular organisation, cortical development and myelination shape the form and function of our arguably most complex and outstanding organ. Diffusion weighted MRI (dMRI) has been extensively used to study the rapid changes in microstructural properties of white and grey matter non-invasively and provides contrast that is complementary to other imaging modalities [Yoshida et al., 2013]. The sensitivity to processes on the cellular level has made diffusion imaging a tool for studying white matter development and the early detection of injury [Hüppi, Dubois, 2006]. Linking the measured signal to changes in the cellular composition and organisation of brain tissue poses data processing challenges unique to the pediatric population. In particular, movement during the acquisition corrupts diffusion images beyond repair and requires manual data cleaning. We developed a neural network classifier that can perform this task automatically, allowing large-scale automated processing and analysis of diffusion data. Also, inferring cellular tissue properties from the signal is difficult as the brain simul-taneously undergoes a number processes that could alter the contrast in various ways. In simulations, I investigate the validity of often implicitly assumed relations between quantities derived from Diffusion Tensor Imaging (DTI) and myelination in the context of changing tissue compartment volume fractions, showing that the interpretation of DTI parameters is flawed in the absence of a-priori knowledge about tissue microstructure. In recent years, progress in acquisition and reconstruction techniques have facilitated acquiring quantitatively and qualitatively richer diffusion images. Currently, High Angu-lar Resolution Diffusion Imaging (HARDI) and higher order diffusion models are uniquely positioned to capture and characterise developmental and maturation processes. The De-veloping Human Connectome Project (dHCP) is a group effort to advance the field of pediatric MRI and has made possible much of the work in this thesis. The HARDI data acquired as part of the dHCP captures microstructural properties of the developing brain with an unprecedented quality and information content. Characterising tissue properties requires a model that allows inferring processes on the cellular level from HARDI data. To build this model, it is necessary to incorporate domain knowledge about physical and biological properties of brain tissue. Even for adult populations, where brain tissue properties are comparatively static, developing higher order diffusion models that provide microstructure-specific markers is an open research question [Novikov, Kiselev, Jespersen, 2018]. For these reasons, this thesis investigates the use of data-driven techniques for the study of brain development, which do not require explicit a priori models of tissue microstructure, but rather attempt to decompose the observed signal into interpretable components. In chapter 8, we develop tools to produce an unbiased group template of tissue prop-erties at term, using a method that makes few assumptions about the microstructual properties of neonatal brain tissue. However, rapid brain maturation entails changes in tissue properties that require taking the temporal component into account. This term-time template is extended to the longitudinal domain in chapter 9, capturing tissue maturation patterns from 33 to 44 weeks gestational age in the dHCP cohort. Together, these developments pave the way for detailed investigations into the devel-opment of the human brain. These techniques will form the basis for more advanced analyses, and will hopefully provide useful insights not available using existing methods. Parts of this thesis and work related to experiments performed in this thesis have been presented at conferences under the titles "Effect of demyelination on diffusion ten-sor indices: A Monte Carlo simulation study" [Pietsch, Tournier, 2015], "Multi-contrast diffeomorphic non-linear registration of orientation density functions" [Pietsch et al., 2017a], "Transfer learning and convolutional neural net fusion for motion artefact de-tection" [Kelly et al., 2017], "Multi-shell neonatal brain HARDI template" [Pietsch et al., 2017b], and "Longitudinal multi-component HARDI atlas of neonatal white matter" [Pietsch et al., 2018]. A manuscript with the title "A framework for multi-component analysis of diffusion MRI data over the neonatal period" based on chapter 9 is currently under review in NeuroImage.
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Sawiak, Stephen John. "Computational methods for mouse brain phenotyping using MRI." Thesis, University of Cambridge, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.611550.

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Campbell-Washburn, A. E. "Development of MRI methods for experimental disease models." Thesis, University College London (University of London), 2012. http://discovery.ucl.ac.uk/1378548/.

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Magnetic resonance imaging (MRI) is a powerful technique for the in vivo study of experimental disease models. The application of MRI to animal models requires the development of specialized methods which can provide insight into anatomy, function, physiology and specific pathology. This thesis research focused around the development of MRI methods for imaging the mouse heart and other body organs. In this work, single slice arterial spin labelling (ASL) was implemented and optimized for the in vivo measurement of perfusion in the mouse heart. A fast ECG-gated Look-Locker sequence was used for T1 mapping with data logger recordings for the assessment of respiration corruption and additional prospective gating. A variability and repeatability study was performed to assess the applicability of the technique in vivo. This technique was then extended to have multi-slice capabilities through the implementation of a multi-slice cardiac T1 mapping sequence. In order to apply the multi-slice sequence in vivo, a new method of perfusion quantification was developed to compensate for the input function of the blood magnetization. Amyloidosis is a severe condition where amyloidotic fibrils of mis-folded proteins accumulate in the extracellular space. With the development of new therapies, there is an urgent need for sensitive imaging markers for the monitoring of amyloidosis. In this research, the extracellular volume fraction, as measured using equilibrium contrast MRI with primed infusions of gadolinium, was assessed as a marker for the detection of amyloidosis and for the monitoring of amyloid depletion during therapy. Finally, in order to remove spike noise in MRI data sets, a post-processing algorithm was implemented and validated for the removal of RF spikes in k-space Overall, this thesis research presents methodological developments of cardiac and body MRI for the in vivo study of experimental models of disease.
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Books on the topic "MRI methods":

1

Topgaard, Daniel, ed. Advanced Diffusion Encoding Methods in MRI. Cambridge: Royal Society of Chemistry, 2020. http://dx.doi.org/10.1039/9781788019910.

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Peter, Jezzard, Matthews Paul M, and Smith Stephen M, eds. Functional MRI: An introduction to methods. Oxford: Oxford University Press, 2001.

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Westbrook, Catherine. MRI in practice. Oxford [England]: Blackwell Scientific Publications, 1993.

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Westbrook, Catherine. MRI in practice. 2nd ed. Oxford [England]: Blackwell Science, 1998.

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B, Lufkin Robert, ed. Interventional MRI. St. Louis: Mosby, 1999.

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Brown, Mark A. MRI: Basic principles and applications. New York: Wiley-Liss, 1995.

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N, Morelli John, ed. Essentials of clinical MRI. New York: Thieme, 2011.

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Edward, Hendrick R., Russ Paul D, and Simon Jack H, eds. MRI: Principles and artifacts. New York: Raven Press, 1993.

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A, Helms Clyde, ed. Musculoskeletal MRI. 2nd ed. Philadelphia: Saunders, 2009.

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Brown, Mark A. MRI: Basic principles and applications. 4th ed. Hoboken, N.J: Wiley-Blackwell, 2010.

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Book chapters on the topic "MRI methods":

1

Okell, Thomas W., Elke Hattingen, Johannes C. Klein, and Karla L. Miller. "Advanced MRI Methods." In Diseases of the Spinal Cord, 85–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-54209-1_5.

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Anteraper, Sheeba Arnold, Alfonso Nieto-Castanon, and Susan Whitfield-Gabrieli. "Functional MRI Methods." In Neuroimaging in Schizophrenia, 93–112. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-35206-6_5.

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Ouwerkerk, Ronald. "Sodium MRI." In Methods in Molecular Biology, 175–201. Totowa, NJ: Humana Press, 2010. http://dx.doi.org/10.1007/978-1-61737-992-5_8.

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Pine, Alexander B., and Feroze B. Mohamed. "fMRI Scanning Methods." In Functional BOLD MRI, 17–36. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-1995-6_2.

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Binder, Jeffrey R. "fMRI of Language Systems: Methods and Applications." In Functional MRI, 245–77. New York, NY: Springer New York, 2006. http://dx.doi.org/10.1007/0-387-34665-1_10.

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Zhou, Heling, Nuria Arias-Ramos, Pilar López-Larrubia, Ralph P. Mason, Sebastián Cerdán, and Jesús Pacheco-Torres. "Oxygenation Imaging by Nuclear Magnetic Resonance Methods." In Preclinical MRI, 297–313. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7531-0_18.

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Brugger, Peter C. "Methods of Fetal MRI." In Medical Radiology, 65–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/174_2010_29.

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Kennan, R. P. "Gradient Echo and Spin Echo Methods for Functional MRI." In Functional MRI, 127–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-58716-0_12.

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Moonen, C. T. W., and P. Van Gelderen. "Optimal Efficiency of 3D and 2D BOLD Gradient Echo fMRI Methods." In Functional MRI, 161–71. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-58716-0_15.

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Lai, Song, Yingbiao Xu, and E. Mark Haacke. "Rapid Acquisition Methods." In Susceptibility Weighted Imaging in MRI, 619–35. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9780470905203.ch33.

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Conference papers on the topic "MRI methods":

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"MRI SEGMENTATION USING MULTIFRACTAL ANALYSIS AND MRF MODELS." In Computer Vision Methods in Medicine. SciTePress - Science and and Technology Publications, 2007. http://dx.doi.org/10.5220/0002046901010106.

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Nævdal, Geir, Ove Sævareid, and Rolf J. Lorentzen. "DATA ASSIMILATION USING MRI DATA." In VII European Congress on Computational Methods in Applied Sciences and Engineering. Athens: Institute of Structural Analysis and Antiseismic Research School of Civil Engineering National Technical University of Athens (NTUA) Greece, 2016. http://dx.doi.org/10.7712/100016.2101.9975.

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O'Brien, Anthony, and Ferdinando M. Rodriguez Y Baena. "Comparison of denoising methods for synthetic low-field neurological MRI." In THE HAMLYN SYMPOSIUM ON MEDICAL ROBOTICS. The Hamlyn Centre, Imperial College London London, UK, 2023. http://dx.doi.org/10.31256/hsmr2023.39.

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Over the past decade, the resurgence of low-field (LF) magnetic resonance imaging (MRI) sensor systems designed to operate up to 1 tesla range has proven well suited to inspire new solutions and design strategies to address frontline medical challenges where environmental factors are most extreme. Examples of successful low-field MRI devices in resource-limited environments include: (1) classification of infant hydrocephalus in Africa and (2) in remote small hospitals where the low-field scanner travels to the patient's bedside to observe volumetric changes in brain structure [1,2]. These low-field MRI design examples have been effective in leveraging MRI information in the setting where it is used with minimal available resources. In developing countries, access to high-field (HF) MRI is limited and requires support and infrastructure to be used. These lower-cost systems can potentially benefit from many developments that have occurred in higher fields, such as signal-to-noise dependence on static magnetic fields and hardware components (i.e., magnet, gradient coils, etc.) [3]. In addition, improvements in machine learning now provide superior noise reduction compared to traditional methods, resulting in improved performance with smaller size and lower power consumption. With improved access to medical imaging equipment, people around the world who cannot afford it due to the high cost of conventional MRIs will be able to obtain high- quality imaging data with improved contrast resolution and acquisition times. SNR (signal-to-noise ratio) is an important measure of the quality of a signal in low-field MRI. The amount of useful information in a signal compared to background noise directly affects the effectiveness of a low-field scan [4].
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Waks, E., J. L. Prince, and A. S. Douglas. "Cardiac motion simulator for tagged MRI." In Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis. IEEE, 1996. http://dx.doi.org/10.1109/mmbia.1996.534070.

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Seetha J. and S. Selvakumar Raja. "Denoising of MRI images using filtering methods." In 2016 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET). IEEE, 2016. http://dx.doi.org/10.1109/wispnet.2016.7566236.

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Jiang, Shao-Feng, Su-Hua Yang, Zhen Chen, and Cong-Xuan Zhang. "Development of Brain Extraction Methods for MRI." In International Conference on Computer Science and Artificial Intelligence (CSAI2016). WORLD SCIENTIFIC, 2017. http://dx.doi.org/10.1142/9789813220294_0041.

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Abanshina, I., Yu Pirogov, D. Kupriyanov, V. Orlova, Carlos Granja, and Claude Leroy. "Brain Morphometry using MRI in Schizophrenia Patients." In NUCLEAR PHYSICS METHODS AND ACCELERATORS IN BIOLOGY AND MEDICINE: Fifth International Summer School on Nuclear Physics Methods and Accelerators in Biology and Medicine. AIP, 2010. http://dx.doi.org/10.1063/1.3295655.

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Maréchal, Pierre. "Duality for maximum entropy diffusion MRI." In BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING (MAXENT 2014). AIP Publishing LLC, 2015. http://dx.doi.org/10.1063/1.4905980.

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Ozcan, Alpay. "Comparison of the Complete Fourier Direct MRI with existing diffusion weighted MRI methods." In 2011 8th IEEE International Symposium on Biomedical Imaging (ISBI 2011). IEEE, 2011. http://dx.doi.org/10.1109/isbi.2011.5872556.

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Soltanian-Zadeh, H., J. P. Windham, and D. J. Peck. "Optimal linear transformation for MRI feature extraction." In Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis. IEEE, 1996. http://dx.doi.org/10.1109/mmbia.1996.534058.

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Reports on the topic "MRI methods":

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Rosen, Matthew S. New Methods of Low-Field MRI for Application to Traumatic Brain Injury. Fort Belvoir, VA: Defense Technical Information Center, April 2014. http://dx.doi.org/10.21236/ada611880.

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Guo, Jia, Xibin Hu, Lei Yao, Shaomin Lv, Jiahua Lv, Xinyu Wang, Mujie Guo, Yu Kong, Ruihan Liu, and Qingxia Kong. Prognosis After Surgery for Refractory Epilepsy Diagnosed by 18F-FDG PET/MRI. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, November 2022. http://dx.doi.org/10.37766/inplasy2022.11.0049.

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Review question / Objective: The purpose of this study was to examine the prognostic status of PET/MRI on surgery in patients with refractory epilepsy, and the methods chosen were randomized controlled trials, cohort studies, and case series of >15 patients. Condition being studied: Medically intractable epilepsy, characterized by recurrent episodes of tonicity, disorientation, spasms, and convulsions, affects 1-2% of the population because treatment trials with 3 or more different antiepileptic drugs have failed. Patients are selected for PET mainly because other standard noninvasive tests (especially MRI and EEG) fail to provide sufficiently reliable localization to allow precise excision of the epileptogenic zone and a good prognosis.
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Thomas Austin, Evan, Paul Kang, Chinedu Mmeje, Joseph Mashni, Mark Brenner, Phillip Koo, and John C Chang. Validation of PI-RADS v2 Scores at Various Non-University Radiology Practices. Science Repository, December 2021. http://dx.doi.org/10.31487/j.aco.2021.02.02.

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Purpose: The purpose of this study was to validate the second version of the Prostate Imaging Reporting and Data System (PI-RADSv2) scores in predicting positive in-bore MRI-guided targeted prostate biopsy results across different non-university related institutions. The study focuses on PI-RADS v2 scoring because during the study period, PI-RADS v2.1 had not been released. Materials and Methods: This was a retrospective review of 147 patients who underwent multiparametric magnetic resonance imaging (mpMRI) of the pelvis followed by in-bore MRI-guided targeted prostate biopsy from December 2014 to May 2018. All lesions on mpMRI were rated according to PI-RADS v2 criteria. PI-RADS v2 scores were then compared to MR-guided biopsy results and pre-biopsy PSA values. Results: Prostate Cancer (PCa) was detected in 54% (80/147) of patients, with more prostate cancer being detected with each subsequent increase in PI-RADS scores. Specifically, biopsy results in patients with PI-RADS 3, 4, and 5 lesions resulted in PCa in 25.6% (10/39), 58.1% (33/55), and 86.0% (37/43) respectively. Clinically significant PCa (Gleason score ≥7) was detected in 17.9% (7/39), 52.7% (29/55), and 72% (31/43) of cases for PI-RADS 3, 4, and 5 lesions respectively. When the PI-RADS scoring and biopsy results were compared across different institutions, there was no difference in the PI-RADS scoring of lesions or in the positive biopsy rates of the lesions. The sensitivity, specificity, PPV, and NPV for PI-RADS 3-4 lesions were also not statistically different across the institutions for detecting Gleason 7 or greater lesions. Conclusion: Our results agree with prior studies that higher PI-RADS scores are associated with the presence of clinically significant PCa and suggest prostate lesions with PI-RADS scores 3-5 have sufficient evidence to warrant targeted biopsy. The comparison of PI-RADS score across different types of non-university practices revealed no difference in scoring and biopsy outcome, suggesting that PI-RADS v2 can be easily applied outside of the university medical center setting. Clinical Relevance: PI-RADS v2 can be applied homogeneously in the non-university setting without significant difference in outcome.
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Alberts, Christopher, and Audrey Dorofee. Mission Risk Diagnostic (MRD) Method Description. Fort Belvoir, VA: Defense Technical Information Center, February 2012. http://dx.doi.org/10.21236/ada611114.

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George, Grant, and Hawley. PR-015-13611-R01 Evaluation of Selected Sampling Techniques on Hydrocarbon-Wet Gas Streams. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), December 2014. http://dx.doi.org/10.55274/r0010403.

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This project evaluated selected single-phase gas sampling methods as candidates for use in sampling hydrocarbon-wet gas streams and obtaining representative samples of only the gas phase, rather than samples of both the gas and liquid. Two spot sampling methods, the helium �pop� method and the floating piston cylinder method, were chosen for evaluation. To capture samples of only the gas phase required one or more arrangements for separating liquids from the sample stream. To this end, a coalescing filter and a vortex separator were chosen for testing with the two sampling methods. The various sampling approaches were tested using the Sampling Method Performance Verification Procedure of API MPMS Chapter 14.1, Appendix F, adapted as appropriate for use in hydrocarbon-wet gas streams. Preliminary tests at SwRI�s Metering Research Facility (MRF) were used to identify possible problems with the equipment and sampling procedures, so that the equipment and procedures could be corrected before the formal tests were conducted. The formal tests were performed at a field site carrying a hydrocarbon-wet gas stream from a shale formation. Results of the formal tests produced recommendations to improve the general ability of the chosen wet-gas sampling method to capture accurate samples of the gas phase, as well as recommended changes to the API Sampling Verification Procedure for testing wet-gas sampling methods.
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Goldstein, Neal. Epidemiology Blog of Neal D. Goldstein, PhD, MBI. Neal D. Goldstein, 2023. http://dx.doi.org/10.17918/goldsteinepi.

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Musings on topics related to epidemiology, epidemiological methods, public and clinical health. Written by Neal D. Goldstein, PhD, MBI. Dr. Goldstein is an Associate Professor of Epidemiology at the Drexel University Dornsife School of Public Health. With a background in biomedical informatics, he focuses on computational approaches in complex data settings, especially electronic health records and disease surveillance, to understand infectious disease transmission. This has been demonstrated through his work with blood borne pathogens (HIV and hepatitis C), COVID-19, vaccine preventable diseases, and healthcare associated infections.
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Ferrell, Christopher E., John M. Eells, David Reinke, and Richard Lee. Metropolitan Transportation Commission Discretionary Transit Funding Methods Evaluation. Mineta Transporation Institute, October 2023. http://dx.doi.org/10.31979/mti.2023.2133.

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In 2021, the Santa Clara Valley Transportation Authority (VTA) approached the Mineta Transportation Institute (MTI) with a proposal to have MTI provide an evaluation of the Metropolitan Transportation Commission’s (MTC’s) operational discretionary funding allocation policies and methods for Bay Area transit operators. The research was done in two parts. Part 1 investigated MTC’s past and current allocation methods for discretionary operational transit funding programs; Part 2 involved the evaluation of outcomes if MTC employed alternative allocation methods. After the Part 1 review of MTC’s various transit funding programs, the federal pandemic relief funds and the Transportation Development Act/State Transit Assistance (TDA/STA) funding programs were selected and evaluated in Part 2 using a set of five alternative allocation metrics and compared to actual MTC allocations. Key findings include: (1) the population-based metric produced the largest increase for VTA’s pandemic relief funds, with VTA receiving 221 percent more than MTC actually allocated in 2020 and 2021, but the San Francisco Municipal Transportation Agency (SFMTA) receiving 64 percent less; (2) the ridership-based metric yielded the smallest amount of VTA pandemic funding, but high ridership operators such as SFMTA would have a 41 percent increase; (3) the population-based metric produced the largest increase in STA funding to VTA but would come at the expense of other transit operators, with Sonoma County receiving 51 percent less; and (4) the ridership-based metric yielded the smallest amount of STA funds for VTA, with 50 percent less funding than actual, while high ridership operators such as SFMTA, would see a roughly 400 percent increase. Thoroughly investigating current and alternative funding allocation methods and policies is critical to understanding their effects on transit agencies and the communities they serve.
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Shani, Uri, Lynn Dudley, Alon Ben-Gal, Menachem Moshelion, and Yajun Wu. Root Conductance, Root-soil Interface Water Potential, Water and Ion Channel Function, and Tissue Expression Profile as Affected by Environmental Conditions. United States Department of Agriculture, October 2007. http://dx.doi.org/10.32747/2007.7592119.bard.

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Constraints on water resources and the environment necessitate more efficient use of water. The key to efficient management is an understanding of the physical and physiological processes occurring in the soil-root hydraulic continuum.While both soil and plant leaf water potentials are well understood, modeled and measured, the root-soil interface where actual uptake processes occur has not been sufficiently studied. The water potential at the root-soil interface (yᵣₒₒₜ), determined by environmental conditions and by soil and plant hydraulic properties, serves as a boundary value in soil and plant uptake equations. In this work, we propose to 1) refine and implement a method for measuring yᵣₒₒₜ; 2) measure yᵣₒₒₜ, water uptake and root hydraulic conductivity for wild type tomato and Arabidopsis under varied q, K⁺, Na⁺ and Cl⁻ levels in the root zone; 3) verify the role of MIPs and ion channels response to q, K⁺ and Na⁺ levels in Arabidopsis and tomato; 4) study the relationships between yᵣₒₒₜ and root hydraulic conductivity for various crops representing important botanical and agricultural species, under conditions of varying soil types, water contents and salinity; and 5) integrate the above to water uptake term(s) to be implemented in models. We have made significant progress toward establishing the efficacy of the emittensiometer and on the molecular biology studies. We have added an additional method for measuring ψᵣₒₒₜ. High-frequency water application through the water source while the plant emerges and becomes established encourages roots to develop towards and into the water source itself. The yᵣₒₒₜ and yₛₒᵢₗ values reflected wetting and drying processes in the rhizosphere and in the bulk soil. Thus, yᵣₒₒₜ can be manipulated by changing irrigation level and frequency. An important and surprising finding resulting from the current research is the obtained yᵣₒₒₜ value. The yᵣₒₒₜ measured using the three different methods: emittensiometer, micro-tensiometer and MRI imaging in both sunflower, tomato and corn plants fell in the same range and were higher by one to three orders of magnitude from the values of -600 to -15,000 cm suggested in the literature. We have added additional information on the regulation of aquaporins and transporters at the transcript and protein levels, particularly under stress. Our preliminary results show that overexpression of one aquaporin gene in tomato dramatically increases its transpiration level (unpublished results). Based on this information, we started screening mutants for other aquaporin genes. During the feasibility testing year, we identified homozygous mutants for eight aquaporin genes, including six mutants for five of the PIP2 genes. Including the homozygous mutants directly available at the ABRC seed stock center, we now have mutants for 11 of the 19 aquaporin genes of interest. Currently, we are screening mutants for other aquaporin genes and ion transporter genes. Understanding plant water uptake under stress is essential for the further advancement of molecular plant stress tolerance work as well as for efficient use of water in agriculture. Virtually all of Israel’s agriculture and about 40% of US agriculture is made possible by irrigation. Both countries face increasing risk of water shortages as urban requirements grow. Both countries will have to find methods of protecting the soil resource while conserving water resources—goals that appear to be in direct conflict. The climate-plant-soil-water system is nonlinear with many feedback mechanisms. Conceptual plant uptake and growth models and mechanism-based computer-simulation models will be valuable tools in developing irrigation regimes and methods that maximize the efficiency of agricultural water. This proposal will contribute to the development of these models by providing critical information on water extraction by the plant that will result in improved predictions of both water requirements and crop yields. Plant water use and plant response to environmental conditions cannot possibly be understood by using the tools and language of a single scientific discipline. This proposal links the disciplines of soil physics and soil physical chemistry with plant physiology and molecular biology in order to correctly treat and understand the soil-plant interface in terms of integrated comprehension. Results from the project will contribute to a mechanistic understanding of the SPAC and will inspire continued multidisciplinary research.
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Wu, Bin, Lixia Guo, Kaikai Zhen, and Chao Sun. Diagnostic and prognostic value of miRNAs in hepatoblastoma: A systematic review with meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, November 2021. http://dx.doi.org/10.37766/inplasy2021.11.0045.

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Review question / Objective: Background and aim: Increasing evidence has revealed the valuable diagnostic and prognostic applications of dysregulated microRNAs (miRNAs) in hepatoblastoma (HB), the most common hepatic malignancy during childhood. However, these results are inconsistent and remain to be elucidated. In the present study, we aimed to systematically compile up-to-date information regarding the clinical value of miRNAs in HB. Methods: Articles concerning the diagnostic and prognostic value of single miRNAs for HB were searched from databases. The sensitivity (SEN), specificity (SPE), positive and negative likelihood ratios (PLR and NLR), diagnostic odds ratio (DOR), area under the curve (AUC), and hazard ratios (HRs) were separately pooled to explore the diagnostic and prognostic performance of miRNA. Subgroup and meta-regression analyses were further carried out only in the event of heterogeneity. Results: In all, 20 studies, involving 264 HB patients and 206 healthy individuals, met the inclusion criteria in the six included literature articles. For the diagnostic analysis of miRNAs in HB, the pooled SEN and SPE were 0.76 (95% CI: 0.72–0.80) and 0.75 (95% CI: 0.70–0.80), respectively. Moreover, the pooled PLR was 2.79 (95% CI: 2.12–3.66), NLR was 0.34 (95% CI: 0.26–0.45), DOR was 10.24 (95% CI: 6.55–16.00), and AUC was 0.83, indicating that miRNAs had moderate diagnostic value in HB. For the prognostic analysis of miRNAs in HB, the abnormal expressions of miR-21, miR-34a, miR-34b, miR-34c, miR-492, miR-193, miR-222, and miR-224 in patients were confirmed to be associated with a worse prognosis. The pooled HR was 1.74 (95% CI: 1.20–2.29) for overall survival (OS) and 1.74 (95% CI: 1.31–2.18) for event-free survival (EFS), suggesting its potential as a prognostic indicator for HB. Conclusion: To the best of our knowledge, this is the first comprehensive systematic review and meta-analysis that examines the diagnostic and prognostic role of dysregulated miRNAs in HB patients. The combined meta-analysis results supported the previous individual finds that miRNAs might provide a new, noninvasive method for the diagnostic and prognostic analyses ofHB.
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Ward, Andrew, Anthony Falls, and Craig Rutland. Development of smartphone-based semi-prepared runway operations (SPRO) models and methods. Engineer Research and Development Center (U.S.), December 2021. http://dx.doi.org/10.21079/11681/42500.

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The U.S. Army Engineer Research and Development Center (ERDC) has developed a method for predicting surface friction response by use of ground vehicles equipped with deceleration-based measurement devices. Specifically, the ERDC has developed models and measurement methods between the Findlay Irvine Mk2 GripTester and a variety of deceleration measurement devices: Bowmonk AFM2 Mk3, Xsens MTi-G-710, two Android smartphones, and two iOS smartphones. These models show positive correlation between ground vehicle deceleration and fixed-slip surface continuous surface friction measurement. This effort extends prior work conducted by the U.S. Army ERDC in developing highly correlative models between the Findlay Irvine Mk2 GripTester and actual C-17 braking deceleration, measured via the runway condition rating (RCR) system. The models and measurement methods detailed here are of considerable use to semi-prepared airfield managers around the world needing to measure safe landing conditions following inclement weather. This work provides the tools necessary for airfield managers to quantify safe landing conditions for C-17 aircraft by using easily obtainable equipment and simple test standards.

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