Chaithya GR's participation in NUMERICS project and beyond

Fellow's Story

Published on 25 September 2023

Chaithya GILIYAR RADHAKRISHNA, ha sstarted his experience as NUMERICS phd fellow on november 2020 at NeuroSpin (Université Paris-Saclay, CEA),Since then he has published several scientific articles and is a co-author of two patents (in validation proces), list below .

Chaithya GILIYAR RADHAKRISHNA : PhD research topic: Designing and learning non-Cartesian k-space sampling trajectories for accelerated 3D MRI. defence on 2023/04/25

Chaithya GR has shared his opinion and experience issue his participation in the NUMERICS project:

My tenure as a fellow in the NUMERICS PhD program under the MSCA Horizon 2020 has been a transformative experience, and I am profoundly grateful for the opportunities it has afforded me. Nestled within the vibrant research environment of Neurospin, CEA Paris Saclay, I had the privilege of delving into a optimizing MRI acquisition and reconstruction, rendering it faster and more efficient. The collaborative atmosphere at CEA, made possible by NUMERICS, has been instrumental in shaping my journey. I extend my heartfelt appreciation to my dedicated supervisors, NUMERICS and CEA for their unwavering support.

One of the standout aspects of this fellowship was the invaluable platform that Neuospin at CEA, provided with access to state-of-the-art MRI scanners. I was able to conduct experiments at the forefront of MRI research, pushing the boundaries of what is achievable in this field. Furthermore, CEA's strong partnerships facilitated an enriching collaboration with industrial partner, resulting in the development of two patents that have not only elevated my research but have also brought us closer to realizing its potential in clinical research and healthcare.

NUMERICS went above and beyond in nurturing my academic and professional growth. Their generous grant of 1000 EUR per year for attending conferences and workshops which allowed me to broaden my horizons and connect with peers and experts across the globe. Additionally, NUMERICS offered diverse courses, ranging from career guidance to project management, which proved invaluable in guiding my research, shaping my thesis, and preparing me for a successful academic and professional trajectory.

These achievements have led me to accept a Research Engineer role (CDI) at INRIA-CEA MIND team, where I look forward to further advancing my research and contributing to the field's growth.

My heartfelt thanks to all who have been part of this incredible journey. NUMERICS has not only enriched my academic pursuits but has also played a pivotal role in propelling my career forward, making this fellowship an invaluable stepping stone in my professional journey.

-Chaithya G R

Publications Patents in pipeline

• Chaithya, G R, G. Daval-Frérot, A. Vignaud and P. Ciuciu. “Method and ap[1]paratus for performing accelerated Magnetic Resonance Imaging with reduced off[1]resonance effect". Patent 1000506640/EP22305592.2. Patent Application: Europe N° 22305592.2. Apr. 2022

• Chaithya, G R, G. Daval-Frérot, A. Vignaud and P. Ciuciu. “Method and apparatus for performing accelerated Magnetic Resonance Imaging through gridded sampling at low frequencies". Patent application in process. Dec. 2022

Accepted articles in Peer-Reviewed Journals

• Chaithya, G R, P. Weiss, A. Massire, A. Vignaud and P. Ciuciu. “Optimizing full 3D SPARKLING trajectories for high-resolution Magnetic Resonance imaging". In: IEEE Transactions on Medical Imaging (Mar. 2022)

• Chaithya, G R and P. Ciuciu. “Jointly learning Non-Cartesian k-space trajectories and reconstruction networks for 2D and 3D MR imaging through projection". In: special issue on AI in MRI: Frontiers and Applications, Bioengineering

• Z. Ramzi, Chaithya, G R, J.-L. Starck and P. Ciuciu. “Density-Compensated Unrolled Networks for 2D and 3D non-Cartesian MRI Reconstruction". In: IEEE Transactions on Medical Imaging (Jan. 2022)

• L. El Gueddari, Chaithya, G R, E. Chouzenoux and P. Ciuciu. “Calibration-Less Multi-Coil Compressed Sensing Magnetic Resonance Image Reconstruction Based on OSCAR Regularization". In: Journal of Imaging 7.3 (2021)

• S. Farrens, A. Grigis, L. El Gueddari, Z. Ramzi, Chaithya, G R, S. Starck, B. Sarthou, H. Cherkaoui, P. Ciuciu and J.-L. Starck. “PySAP: Python Sparse Data Analysis Package for multidisciplinary image processing". In: Astronomy and Computing 32 (2020), p. 100402

Articles in pipeline to Peer-Reviewed Journals

• Chaithya, G R, G. Daval-Frérot, A. Massire, A. Vignaud and P. Ciuciu. “Improving SPARKLING trajectories through Minimized Off-Resonance Effects and Gridding of Low Frequencies". In: under review MRM

Accepted papers in Peer-reviewed Conferences

• Chaithya, G R, Z. Ramzi and P. Ciuciu. “Learning the sampling density in 2D SPARKLING MRI acquisition for optimized image reconstruction". In: 29th European Signal Processing Conference (EUSIPCO). Dublin, Ireland, Sept. 2021, pp. 960–964

• Chaithya, G R, Z. Ramzi and P. Ciuciu. “Hybrid learning of Non-Cartesian k-space trajectory and MR image reconstruction networks". In: 2022 IEEE 19th international symposium on biomedical imaging (ISBI). Kolkata, India, Mar. 2022 11 12 CONTENTS

• K. Pooja, Z. Ramzi, Chaithya, G R and P. Ciuciu. “MC-PDNet: Deep Unrolled Neural Network for Multi-contrast MR Image Reconstruction from Undersampled k-space data". In: 2022 IEEE 19th international symposium on biomedical imaging (ISBI). Kolkata, India, Mar. 2022

Abstracts in Peer-reviewed Conferences / Papers in Workshops

• L. E. Gueddari, Chaithya, G R, Z. Ramzi, S. Farrens, S. Starck, A. Grigis, J.-L. Starck and P. Ciuciu. “PySAP-MRI: a Python Package for MR Image Reconstruction". In: ISMRM workshop on Data Sampling and Image Reconstruction. Sedona, AZ, United States, Jan. 2020

• Chaithya, G R and P. Ciuciu. “Benchmarking learned non-Cartesian k-space traject[1]ories and reconstruction networks". In: ISMRM. 3308. London, UK, May 2022

• Chaithya, G R, G. Daval-Frérot, A. Massire, B. Mailhe, M. Nadar, A. Vignaud and P. Ciuciu. “MORE-SPARKLING: Non-Cartesian trajectories with Minimized Off-Resonance Effects". In: ISMRM. 1435. London, UK, May 2022

• Z. Amor, Chaithya, G R, C. Le Ster, G. Daval-Frérot, N. Boulant, F. Mauconduit, C. Mirkes, P. Ciuciu and A. Vignaud. “B0 field distortions monitoring and correction for 3D non-Cartesian fMRI acquisitions using a field camera: Application to 3D[1]SPARKLING at 7T". in: ISMRM. 2822. London, UK, May 2022

• Z. Amor, Chaithya, G R, B. Daval-Frérot G. Thirion, F. Mauconduit, C. Mirkes, P. Ciuciu and A. Vignaud. “Prospects of non-Cartesian 3D-SPARKLING encoding for functional MRI: A preliminary case study for retinotopic mapping". In: ISMRM. 2823. London, UK, May 2022

• Z. Amor, Chaithya, G R, B. Daval-Frérot G. Thirion, F. Mauconduit, P. Ciuciu and A. Vignaud. “3D SPARKLING for functional MRI: A pilot study for retinotopic mapping at 7T". in: 30th proceedings of ISMRM. Glasgow, Scotland, UK, 2022

• R. Baptista, A. Vignaud, Chaithya, G R, G. Daval-Frérot, F. Mauconduit, M. Naudin, M. Lapert, R. Guillevin, P. Ciuciu, C. Lerman-Rabrait and F. Boumezbeur. “Evaluation of 3D SPARKLING readout for Sodium UTE MRI at ultra-high magnetic field". In: ISMRM. London, UK, May 2022

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