Search Results - "R, Chaithya G"

NC-PDNet: A Density-Compensated Unrolled Network for 2D and 3D Non-Cartesian MRI Reconstruction by Ramzi, Zaccharie, G R, Chaithya, Starck, Jean-Luc, Ciuciu, Philippe

“…Deep Learning has become a very promising avenue for magnetic resonance image (MRI) reconstruction. In this work, we explore the potential of unrolled networks…”
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Non-Cartesian 3D-SPARKLING vs Cartesian 3D-EPI encoding schemes for functional Magnetic Resonance Imaging at 7 Tesla by Amor, Zaineb, Ciuciu, Philippe, G R, Chaithya, Daval-Frérot, Guillaume, Mauconduit, Franck, Thirion, Bertrand, Vignaud, Alexandre

“…The quest for higher spatial and/or temporal resolution in functional MRI (fMRI) while preserving a sufficient temporal signal-to-noise ratio (tSNR) has…”
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Optimizing Full 3D SPARKLING Trajectories for High-Resolution Magnetic Resonance Imaging by Chaithya, G. R., Weiss, Pierre, Daval-Frerot, Guillaume, Massire, Aurelien, Vignaud, Alexandre, Ciuciu, Philippe

“…The Spreading Projection Algorithm for Rapid K-space sampLING, or SPARKLING, is an optimization-driven method that has been recently introduced for accelerated…”
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Impact of B0$$ {\mathrm{B}}_0 $$ field imperfections correction on BOLD sensitivity in 3D‐SPARKLING fMRI data by Amor, Zaineb, Le Ster, Caroline, GR, Chaithya, Daval‐Frérot, Guillaume, Boulant, Nicolas, Mauconduit, Franck, Thirion, Bertrand, Ciuciu, Philippe, Vignaud, Alexandre

“…Purpose Static and dynamic B0$$ {\mathrm{B}}_0 $$ field imperfections are detrimental to functional MRI (fMRI) applications, especially at ultra‐high magnetic…”
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Hybrid Learning of Non-Cartesian K-Space Trajectory and Mr Image Reconstruction Networks by G R, Chaithya, Ramzi, Zaccharie, Ciuciu, Philippe

“…Compressed sensing (CS) in Magnetic resonance Imaging (MRI) essentially involves the optimization of 1) the sampling pattern in k-space under MR hardware…”
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A Multi-Center Study on Human Brain Glutathione Conformation using Magnetic Resonance Spectroscopy by Shukla, Deepika, Mandal, Pravat K, Ersland, Lars, Grüner, Eli Renate, Tripathi, Manjari, Raghunathan, Partha, Sharma, Ankita, Chaithya, G R, Punjabi, Khushboo, Splaine, Christopher

“…Molecular dynamics simulation and in vitro nuclear magnetic resonance (NMR) studies on glutathione (GSH) indicated existence of closed and extended…”
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Learning the sampling density in 2D SPARKLING MRI acquisition for optimized image reconstruction by Chaithya, G R, Ramzi, Zaccharie, Ciuciu, Philippe

“…The SPARKLING algorithm was originally developed for accelerated 2D magnetic resonance imaging (MRI) in the compressed sensing (CS) context. It yields…”
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Impact of B0 field imperfections correction on BOLD sensitivity in 3D‐SPARKLING fMRI data by Amor, Zaineb, Le Ster, Caroline, Gr, Chaithya, Daval-Frérot, Guillaume, Boulant, Nicolas, Mauconduit, Franck, Thirion, Bertrand, Ciuciu, Philippe, Vignaud, Alexandre

“…Purpose: Static and dynamic field imperfections are detrimental to functional MRI (fMRI) applications, especially at ultra‐high magnetic fields (UHF). In this…”
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PySAP: Python Sparse Data Analysis Package for Multidisciplinary Image Processing by Farrens, S, Grigis, A, Gueddari, L. El, Ramzi, Z, R, Chaithya G, Starck, S, Sarthou, B, Cherkaoui, H, Ciuciu, P, Starck, J. -L

“…Astronomy and Computing, Volume 32, July 2020, 100402 We present the open-source image processing software package PySAP (Python Sparse data Analysis Package)…”
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MC-PDNet: Deep Unrolled Neural Network For Multi-Contrast Mr Image Reconstruction From Undersampled K-Space Data by Pooja, Kumari, Ramzi, Zaccharie, Chaithya, G.R., Ciuciu, Philippe

“…Multi-contrast (MC) MR images are similar in structure and can leverage anatomical structure to perform joint reconstruction especially from a limited number…”
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PySAP: Python Sparse Data Analysis Package for multidisciplinary image processing by Farrens, S., Grigis, A., El Gueddari, L., Ramzi, Z., G.R., Chaithya, Starck, S., Sarthou, B., Cherkaoui, H., Ciuciu, P., Starck, J.-L.

“…We present the open-source image processing software package PySAP (Python Sparse data Analysis Package) developed for the COmpressed Sensing for Magnetic…”
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Irm cerebrale du sodium rapide avec sparkling 3d sous-echantillonnee à 7 tesla by Baptista, Renata Porciuncula, Naudin, Mathieu, R, Chaithya G, Daval-Frerot, Guillaume, Mauconduit, Franck, Haeger, Alexa, Romanzetti, Sandro, Lapert, Marc, Ciuciu, Philippe, Rabrait-Lerman, Cecile, Guillevin, Remy, Vignaud, Alexandre, Boumezbeur, Fawzi

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Benchmarking learned non-Cartesian k-space trajectories and reconstruction networks by R, Chaithya G, Ciuciu, Philippe

“…We benchmark the current existing methods to jointly learn non-Cartesian k-space trajectory and reconstruction: PILOT, BJORK, and compare them with those…”
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Irm cerebrale du sodium rapide avec sparkling 3d sous-echantillonnee à 7 tesla by Baptista, Renata Porciuncula, Naudin, Mathieu, R, Chaithya G, Daval-Frerot, Guillaume, Mauconduit, Franck, Haeger, Alexa, Romanzetti, Sandro, Lapert, Marc, Ciuciu, Philippe, Rabrait-Lerman, Cecile, Guillevin, Remy, Vignaud, Alexandre, Boumezbeur, Fawzi

“…L'imagerie RMN du sodium (23Na) a démontrée à travers plusieurs études sa pertinence en tant que biomarqueur de viabilité cellulaire en particulier dans les…”
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Hybrid learning of Non-Cartesian k-space trajectory and MR image reconstruction networks by R, Chaithya G, Ramzi, Zaccharie, Ciuciu, Philippe

“…Compressed sensing (CS) in Magnetic resonance Imaging (MRI) essentially involves the optimization of 1) the sampling pattern in k-space under MR hardware…”
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Learning the sampling density in 2D SPARKLING MRI acquisition for optimized image reconstruction by R, Chaithya G, Ramzi, Zaccharie, Ciuciu, Philippe

“…The SPARKLING algorithm was originally developed for accelerated 2D magnetic resonance imaging (MRI) in the compressed sensing (CS) context. It yields…”
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Optimizing full 3D SPARKLING trajectories for high-resolution T2-weighted Magnetic Resonance Imaging by R, Chaithya G, Weiss, Pierre, Daval-Frérot, Guillaume, Massire, Aurélien, Vignaud, Alexandre, Ciuciu, Philippe

“…The Spreading Projection Algorithm for Rapid K-space samplING, or SPARKLING, is an optimization-driven method that has been recently introduced for accelerated…”
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Data transfer using MCM code by Manishkumar, Shah Palash, Agarawal, Deepesh J., Tom, Ajin Jiji, Chaithya, G. R., Varambally, Samhita

“…Multicolored Matrix (MCM) Code is a two-dimensional color coded matrix. It consists a sequence of images rendered at an optimum frame rate to transfer simple…”
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