Back to the list
Congress: ECR25
Poster Number: C-10894
Type: Poster: EPOS Radiologist (scientific)
Authorblock: Y. J. Heo; Busan/KR
Disclosures:
Young Jin Heo: Nothing to disclose
Keywords: CNS, MR, Imaging sequences, Neoplasia
References
  1. Almansour H, Gassenmaier S, Nickel D, Kannengiesser S, Afat S, Weiss J, et al. Deep learning-based superresolution reconstruction for upper abdominal magnetic resonance imaging: an analysis of image quality, diagnostic confidence, and lesion conspicuity. Investigative radiology. 2021;56(8):509-16.
  2. Chaika M, Afat S, Wessling D, Afat C, Nickel D, Kannengiesser S, et al. Deep learning-based super-resolution gradient echo imaging of the pancreas: Improvement of image quality and reduction of acquisition time. Diagn Interv Imaging. 2023;104(2):53-9.
  3. Almansour H, Herrmann J, Gassenmaier S, Lingg A, Nickel MD, Kannengiesser S, et al. 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. Acad Radiol. 2023;30(5):863-72.
  4. Kim E, Cho H-H, Cho S, Park B, Hong J, Shin K, et al. Accelerated synthetic MRI with deep learning–based reconstruction for pediatric neuroimaging. American Journal of Neuroradiology. 2022;43(11):1653-9.
  5. Park JE, Choi YH, Cheon J-E, Kim WS, Kim I-O, Ryu YJ, et al. Three-dimensional radial VIBE sequence for contrast-enhanced brain imaging: an alternative for reducing motion artifacts in restless children. American Journal of Roentgenology. 2018;210(4):876-82.
GALLERY