Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Gregor, Koerzdoerfer"'
Autor:
Judith Herrmann, You-Shan Feng, Sebastian Gassenmaier, Jan-Peter Grunz, Gregor Koerzdoerfer, Andreas Lingg, Haidara Almansour, Dominik Nickel, Ahmed E. Othman, Saif Afat
Publikováno v:
European Journal of Radiology Open, Vol 12, Iss , Pp 100557- (2024)
Purpose: The objective of this study was to implement a 5-minute MRI protocol for the shoulder in routine clinical practice consisting of accelerated 2D turbo spin echo (TSE) sequences with deep learning (DL) reconstruction at 1.5 and 3 Tesla, and to
Externí odkaz:
https://doaj.org/article/034153336cf7428989428ce8738241eb
Autor:
Judith Herrmann, Saif Afat, Sebastian Gassenmaier, Gregor Koerzdoerfer, Andreas Lingg, Haidara Almansour, Dominik Nickel, Sebastian Werner
Publikováno v:
Diagnostics, Vol 13, Iss 20, p 3241 (2023)
Objectives: Hip MRI using standard multiplanar sequences requires long scan times. Accelerating MRI is accompanied by reduced image quality. This study aimed to compare standard two-dimensional (2D) turbo spin echo (TSE) sequences with accelerated 2D
Externí odkaz:
https://doaj.org/article/1003accbbc774e11a955f734dcf85acf
Autor:
Seunghyeon Roh, Jae In Park, Gun Young Kim, Hye Jin Yoo, Dominik Nickel, Gregor Koerzdoerfer, JaeKon Sung, Jiseon Oh, Hee Dong Chae, Sung Hwan Hong, Ja-Young Choi
Publikováno v:
PLoS ONE, Vol 18, Iss 6, p e0287903 (2023)
ObjectiveTo evaluate the feasibility and clinical usefulness of deep learning (DL)-accelerated turbo spin echo (TSEDL) sequences relative to standard TSE sequences (TSES) for acute radius fracture patients wearing a splint.MethodsThis prospective con
Externí odkaz:
https://doaj.org/article/86dad51e327445d0b53e6a9d45ccfb54
Autor:
Judith Herrmann, Saif Afat, Sebastian Gassenmaier, Jan-Peter Grunz, Gregor Koerzdoerfer, Andreas Lingg, Haidara Almansour, Dominik Nickel, Theresa Sophie Patzer, Sebastian Werner
Publikováno v:
Diagnostics, Vol 13, Iss 17, p 2747 (2023)
Objective: The objective of this study was to evaluate a deep learning (DL) reconstruction for turbo spin echo (TSE) sequences of the elbow regarding image quality and visualization of anatomy. Materials and Methods: Between October 2020 and June 202
Externí odkaz:
https://doaj.org/article/8d592a6935c04e118a4172080574eb51
Autor:
Gabriel Keller, Arne Estler, Judith Herrmann, Saif Afat, Ahmed E. Othman, Dominik Nickel, Gregor Koerzdoerfer, Fabian Springer
Publikováno v:
La radiologia medica. 128:347-356
Purpose Magnetic resonance imaging (MRI) scan time remains a limited and valuable resource. This study evaluates the diagnostic performance of a deep learning (DL)-based accelerated TSE study protocol compared to a standard TSE study protocol in ankl
Autor:
Elisabeth Springer, Pedro Lima Cardoso, Bernhard Strasser, Wolfgang Bogner, Matthias Preusser, Georg Widhalm, Mathias Nittka, Gregor Koerzdoerfer, Pavol Szomolanyi, Gilbert Hangel, Johannes A. Hainfellner, Wolfgang Marik, Siegfried Trattnig
Publikováno v:
Cancers, Vol 14, Iss 3, p 723 (2022)
(1) Background: Advanced MR imaging (MRI) of brain tumors is mainly based on qualitative contrast images. MR Fingerprinting (MRF) offers a novel approach. The purpose of this study was to use MRF-derived T1 and T2 relaxation maps to differentiate dif
Externí odkaz:
https://doaj.org/article/caf648451055446da852203754d980e4
Autor:
Xinhui Wang, Rui Zhang, Gregor Koerzdoerfer, Mathias Nittka, Xianchang Zhang, Meiyun Wang, Yan Bai, Qiyong Gong
Publikováno v:
Academic Radiology. 29:e157-e165
Preoperative meningioma consistency prediction is highly beneficial for surgical planning and prognostication. We aimed to use magnetic resonance fingerprinting (MRF)-derived T1 and T2 values to preoperatively predict meningioma consistency.A total o
Autor:
Judith Herrmann, Gregor Koerzdoerfer, Dominik Nickel, Mahmoud Mostapha, Mariappan Nadar, Sebastian Gassenmaier, Thomas Kuestner, Ahmed E. Othman
Publikováno v:
Diagnostics, Vol 11, Iss 8, p 1484 (2021)
Magnetic Resonance Imaging (MRI) of the musculoskeletal system is one of the most common examinations in clinical routine. The application of Deep Learning (DL) reconstruction for MRI is increasingly gaining attention due to its potential to improve
Externí odkaz:
https://doaj.org/article/293f5898eaf04f24b320766bb135a989
Autor:
Geojeong Seo, Sun Joo Lee, Dae Hyun Park, Sung Hwa Paeng, Gregor Koerzdoerfer, Marcel Dominik Nickel, Jaekon Sung
Publikováno v:
Skeletal Radiology.
Autor:
Haidara Almansour, Judith Herrmann, Sebastian Gassenmaier, Saif Afat, Johann Jacoby, Gregor Koerzdoerfer, Dominik Nickel, Mahmoud Mostapha, Mariappan Nadar, Ahmed E. Othman
Publikováno v:
Radiology. 306
Background Deep learning (DL)-based MRI reconstructions can reduce examination times for turbo spin-echo (TSE) acquisitions. Studies that prospectively employ DL-based reconstructions of rapidly acquired, undersampled spine MRI are needed. Purpose To