Her main research concerns Undersampling, Image quality, Artificial intelligence, Computer vision and Compressed sensing. Her Image quality research is multidisciplinary, relying on both Sampling, Imaging phantom, Coronary arteries, Cartesian coordinate system and Biomedical engineering. Her Artificial intelligence research integrates issues from Magnetic resonance imaging and Affine transformation.
Her work in Computer vision addresses subjects such as k-space, which are connected to disciplines such as Structure from motion, Encoding and Motion compensation. Her work in Compressed sensing covers topics such as Sparse approximation which are related to areas like Resolution and Reduction. Her study in Golden angle is interdisciplinary in nature, drawing from both Cine mri and Free breathing.
Claudia Prieto mainly investigates Artificial intelligence, Computer vision, Image quality, Magnetic resonance imaging and Imaging phantom. Claudia Prieto usually deals with Artificial intelligence and limits it to topics linked to Pattern recognition and Regularization and Matching. Her research in Computer vision focuses on subjects like Cartesian coordinate system, which are connected to Affine transformation and Motion.
Her Image quality research incorporates elements of Image resolution, Sampling, Nuclear medicine, Motion estimation and Coronary arteries. In the subject of general Magnetic resonance imaging, her work in Magnetization transfer and Magnetic resonance angiography is often linked to Parametric statistics and High resolution, thereby combining diverse domains of study. Her studies in Imaging phantom integrate themes in fields like Spin echo, T2 mapping, Healthy subjects and Biomedical engineering.
Claudia Prieto spends much of her time researching Artificial intelligence, Imaging phantom, Magnetic resonance imaging, Image quality and Biomedical engineering. Her Artificial intelligence research includes elements of Computer vision and Pattern recognition. She has included themes like Spin echo, T2 mapping, Fat fraction and Nuclear magnetic resonance in her Imaging phantom study.
Her Magnetic resonance imaging research focuses on Angiology and how it relates to Coronary arteries, Image resolution, Rigid motion and Resolution. The various areas that Claudia Prieto examines in her Image quality study include Segmentation, Image segmentation, Scan time, Nuclear medicine and Subpixel rendering. In her research, Wavelet is intimately related to Artificial neural network, which falls under the overarching field of Undersampling.
Claudia Prieto focuses on Imaging phantom, T2 mapping, Biomedical engineering, In patient and Golden angle. The concepts of her T2 mapping study are interwoven with issues in Cardiac magnetic resonance, Nuclear magnetic resonance and Free breathing. Within one scientific family, she focuses on topics pertaining to Sampling under Biomedical engineering, and may sometimes address concerns connected to Image resolution, Cardiomyopathy and Respiratory motion.
Her research in Golden angle tackles topics such as Fat fraction which are related to areas like Liver tissue, Liver disease and Partial volume. Her work deals with themes such as Deep learning and Computer vision, which intersect with Magnetic resonance imaging. Her work carried out in the field of Cine mri brings together such families of science as Image quality and Artificial intelligence.
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Motion corrected compressed sensing for free-breathing dynamic cardiac MRI.
Muhammad Usman;David Atkinson;Freddy Odille;Christoph Kolbitsch.
Magnetic Resonance in Medicine (2013)
Whole-heart coronary MR angiography with 2D self-navigated image reconstruction.
Markus Henningsson;Peter Koken;Christian Stehning;Reza Razavi.
Magnetic Resonance in Medicine (2012)
Highly efficient respiratory motion compensated free‐breathing coronary mra using golden‐step Cartesian acquisition
Claudia Prieto;Claudia Prieto;Mariya Doneva;Muhammad Usman;Markus Henningsson.
Journal of Magnetic Resonance Imaging (2015)
Characterization of Bordetella pertussis growing as biofilm by chemical analysis and FT-IR spectroscopy
A. Bosch;D. Serra;C. Prieto;J. Schmitt.
Applied Microbiology and Biotechnology (2006)
Highly efficient nonrigid motion corrected 3D whole-heart coronary vessel wall imaging
Gastao Cruz;David Atkinson;Markus Henningsson;René Michael Botnar;René Michael Botnar.
Magnetic Resonance in Medicine (2017)
k-t Group sparse: a method for accelerating dynamic MRI.
M. Usman;C. Prieto;T. Schaeffter;P. G. Batchelor.
Magnetic Resonance in Medicine (2011)
Accelerated motion corrected three‐dimensional abdominal MRI using total variation regularized SENSE reconstruction
Gastao Cruz;David Atkinson;Christian Buerger;Tobias Schaeffter.
Magnetic Resonance in Medicine (2016)
Nonrigid Motion Modeling of the Liver From 3-D Undersampled Self-Gated Golden-Radial Phase Encoded MRI
C. Buerger;R. E. Clough;A. P. King;T. Schaeffter.
IEEE Transactions on Medical Imaging (2012)
3D Undersampled Golden-Radial Phase Encoding for DCE-MRA Using Inherently Regularized Iterative SENSE
Claudia Prieto;Sergio Uribe;Sergio Uribe;Reza Razavi;David Atkinson.
Magnetic Resonance in Medicine (2010)
Five-minute whole-heart coronary MRA with sub-millimeter isotropic resolution, 100% respiratory scan efficiency, and 3D-PROST reconstruction.
Aurélien Bustin;Giulia Ginami;Gastão Cruz;Teresa Correia.
Magnetic Resonance in Medicine (2019)
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