Zobrazeno 1 - 10 of 52 pro vyhledávání: '"Simon Arberet"'
1
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
Autor: Luke A. Ginocchio, Paul N. Smereka, Angela Tong, Vinay Prabhu, Dominik Nickel, Simon Arberet, Hersh Chandarana, Krishna P. Shanbhogue
Publikováno v: Abdom Radiol (NY)
PURPOSE: Fat-suppressed T2-weighted imaging (T2-FS) requires a long scan time and can be wrought with motion artifacts, urging the development of a shorter and more motion robust sequence. We compare the image quality of a single-shot T2-weighted MRI
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3eb657b829c1a36aa033e1b27ad71b68
https://doi.org/10.1007/s00261-022-03687-y
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3
A parallel spatial and Bloch manifold regularized iterative reconstruction method for MR Fingerprinting
Autor: Simon Arberet, Peter Speier, Mariappan S. Nadar, Gregor Körzdörfer, Mathias Nittka, Heiko Meyer, Boris Mailhe, Xiao Chen
Publikováno v: Magnetic Resonance Imaging. 82:74-90
Magnetic Resonance Fingerprinting (MRF) reconstructs tissue maps based on a sequence of very highly undersampled images. In order to be able to perform MRF reconstruction, state-of-the-art MRF methods rely on priors such as the MR physics (Bloch equa
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f7a38c4e292274651956d1b82d53a92
https://doi.org/10.1016/j.mri.2021.06.009
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4
Development and Evaluation of Deep Learning-Accelerated Single-Breath-Hold Abdominal HASTE at 3 T Using Variable Refocusing Flip Angles
Autor: Dominik Nickel, Konstantin Nikolaou, Sebastian Gassenmaier, Simon Arberet, Judith Herrmann, Saif Afat, Ahmed E. Othman, John P. Mugler
Publikováno v: Investigative Radiology. 56:645-652
Objective Deep learning (DL) reconstruction enables substantial acceleration of image acquisition while maintaining diagnostic image quality. The aims of this study were to overcome the drawback of specific absorption rate (SAR)-related limitations a
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7372ac5b9d05917fc3dd44ff75d858c0
https://doi.org/10.1097/rli.0000000000000785
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5
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
Autor: Simon Arberet, Hersh Chandarana, Rebecca Anthopolos, Dominik Nickel, Paul Smereka, Angela Tong, Krishna Shanbhogue
Publikováno v: European Radiology. 31:8447-8457
To compare the image quality of an accelerated single-shot T2-weighted fat-suppressed (FS) MRI of the liver with deep learning-based image reconstruction (DL HASTE-FS) with conventional T2-weighted FS sequence (conventional T2 FS) at 1.5 T.One hundre
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e70fadc8d31d6fff81d2214f1a5a34a5
https://doi.org/10.1007/s00330-021-08008-3
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6
Clinical feasibility of accelerated diffusion weighted imaging of the abdomen with deep learning reconstruction: Comparison with conventional diffusion weighted imaging
Autor: Sung Hwan Bae, Jiyoung Hwang, Seong Sook Hong, Eun Ji Lee, Jewon Jeong, Thomas Benkert, JaeKon Sung, Simon Arberet
Publikováno v: European journal of radiology. 154
To assess the clinical feasibility of accelerated deep learning-reconstructed diffusion weighted imaging (DWI) and to compare its image quality and acquisition time with those of conventional DWI.Seventy-four consecutive patients who underwent 3 T ab
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d23fdbd7d41875b39aa9b9374366d42
https://pubmed.ncbi.nlm.nih.gov/35797791
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8
Diagnostic Confidence and Feasibility of a Deep Learning Accelerated HASTE Sequence of the Abdomen in a Single Breath-Hold
Autor: Matthias Kündel, Dominik Nickel, Judith Herrmann, Andreas Lingg, Saif Afat, Sebastian Gassenmaier, Simon Arberet, Ahmed E. Othman
Publikováno v: Investigative Radiology. 56:313-319
OBJECTIVE The aim of this study was to evaluate the feasibility of a single breath-hold fast half-Fourier single-shot turbo spin echo (HASTE) sequence using a deep learning reconstruction (HASTEDL) for T2-weighted magnetic resonance imaging of the ab
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::69ef8d1797c5ab398442bf2a95c6caa4
https://doi.org/10.1097/rli.0000000000000743
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10
Analysis of a Deep Learning-Based Superresolution Algorithm Tailored to Partial Fourier Gradient Echo Sequences of the Abdomen at 1.5 T: Reduction of Breath-Hold Time and Improvement of Image Quality
Autor: Simon Arberet, Sebastian Gassenmaier, Daniel Wessling, Saif Afat, Judith Herrmann, Carmen Afat, Ahmed E. Othman, Dominik Nickel
Publikováno v: Investigative radiology. 57(3)
OBJECTIVES The aim of this study was to investigate the feasibility and impact of a novel deep learning superresolution algorithm tailored to partial Fourier allowing retrospectively theoretical acquisition time reduction in 1.5 T T1-weighted gradien
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ead5465c8884e6477ee597a4ee704525
https://pubmed.ncbi.nlm.nih.gov/34510101
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