Simon Arberet

Siemens (United States) — United States

Computer Science · Physical Sciences

18h-index1.2kcitations55works0.22yr avg

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Speech and Audio Processing(19), Blind Source Separation Techniques(19), Advanced MRI Techniques and Applications(15), Medical Imaging Techniques and Applications(9), Music and Audio Processing(8)

Publications55 total

Single shot full plan deep learning dose computation for radiation therapy using spherical harmonics

Medical Physics·2026Open Access

Sharing a flexible urethral sparing SBRT prostate RapidPlan model and quantifying plan quality via dosimetric scorecard with clinical implementation

Radiation Oncology·2025Open Access

Respiratory triggered abdominal T2-weighted imaging for concurrent T2water mapping and PDFF quantification using RADGRASE

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition·2025

Accelerated free‐breathing abdominal T2 mapping with deep learning reconstruction of radial turbo spin‐echo data

Magnetic Resonance in Medicine·2025Open Access

Beam's eye view to fluence maps 3D network for ultra fast VMAT radiotherapy planning

Medical Physics·2025Open Access

A Beam's Eye View to Fluence Maps 3D Network for Ultra Fast VMAT Radiotherapy Planning

arXiv (Cornell University)·2025Open Access

Automating RT Planning at Scale: High Quality Data For AI Training

1 cited

arXiv (Cornell University)·2025· 1 citedOpen Access

Model-Assisted Deep Learning-Based Reconstruction of Accelerated Golden-Angle Radial Data for Free-Breathing Dynamic Contrast-Enhanced MRI

Free-breathing T2 mapping of the abdomen in half the scan time using RADTSE with deep learning reconstruction

1 cited

Improved Clinical Diffusion Weighted Imaging by Combining Deep Learning Reconstruction, Partial Fourier, and Super Resolution

Deep learning reconstruction of radial T2 weighted data sets with data consistent unrolled neural networks

Multi-Agent Reinforcement Learning Meets Leaf Sequencing in Radiotherapy

arXiv (Cornell University)·2024Open Access

Deep learning HASTE sequence compared with T2-weighted BLADE sequence for liver MRI at 3 Tesla: a qualitative and quantitative prospective study

24 cited

European Radiology·2023· 24 cited

Accelerated T2-weighted MRI of the liver at 3 T using a single-shot technique with deep learning-based image reconstruction: impact on the image quality and lesion detection

19 cited

Abdominal Radiology·2022· 19 citedOpen Access

Combined Deep Learning-based Super-Resolution and Partial Fourier Reconstruction for Gradient Echo Sequences in Abdominal MRI at 3 Tesla: Shortening Breath-Hold Time and Improving Image Sharpness and Lesion Conspicuity

29 cited

Academic Radiology·2022· 29 cited

Clinical feasibility of accelerated diffusion weighted imaging of the abdomen with deep learning reconstruction: Comparison with conventional diffusion weighted imaging

44 cited

European Journal of Radiology·2022· 44 cited

Comprehensive Clinical Evaluation of a Deep Learning-Accelerated, Single-Breath-Hold Abdominal HASTE at 1.5 T and 3 T

22 cited

Academic Radiology·2022· 22 cited

A parallel spatial and Bloch manifold regularized iterative reconstruction method for MR Fingerprinting

3 cited

Magnetic Resonance Imaging·2021· 3 cited

Development and Evaluation of Deep Learning-Accelerated Single-Breath-Hold Abdominal HASTE at 3 T Using Variable Refocusing Flip Angles

45 cited

Investigative Radiology·2021· 45 cited

Accelerated single-shot T2-weighted fat-suppressed (FS) MRI of the liver with deep learning–based image reconstruction: qualitative and quantitative comparison of image quality with conventional T2-weighted FS sequence

65 cited

European Radiology·2021· 65 cited

page 1 of 3Next →

Frequent Co-authors

Rémi Gribonval(15), Dominik Nickel(10), Frédéric Bimbot(9), Pierre Vandergheynst(7), Alexey Ozerov(6), Mariappan S. Nadar(5), Ali Kamen(5), Judith Herrmann(4), Sebastian Gassenmaier(4), Saif Afat(4), Ahmed E. Othman(4), Prasad Sudhakar(4), Jonathan Sackett(4), Florin C. Ghesu(4), Brian Toner(4), Diego R. Martín(4), Vibhas Deshpande(4), Ali Bilgin(4), María I. Altbach(4), Riqiang Gao(4)