Tumor likelihood estimation on MRI prostate data by utilizing k-Space information

Autor: Rempe, M., Hörst, F., Seibold, C., Hadaschik, B., Schlimbach, M., Egger, J., Kröninger, K., Breuer, F., Blaimer, M., Kleesiek, J.

We present a novel preprocessing and prediction pipeline for the classification of magnetic resonance imaging (MRI) that takes advantage of the information rich complex valued k-Space. Using a publicly available MRI raw dataset with 312 subject and a

Externí odkaz: http://arxiv.org/abs/2407.06165

Iterative training of robust k-space interpolation networks for improved image reconstruction with limited scan specific training samples.

Autor: Dawood P; Department of Physics, University of Würzburg, Würzburg, Germany., Breuer F; Magnetic Resonance and X-ray Imaging Department, Fraunhofer Institute for Integrated Circuits IIS, Division Development Center X-Ray Technology, Würzburg, Germany., Stebani J; Magnetic Resonance and X-ray Imaging Department, Fraunhofer Institute for Integrated Circuits IIS, Division Development Center X-Ray Technology, Würzburg, Germany., Burd P; Institute for Theoretical Physics and Astrophysics, University of Würzburg, Würzburg, Germany., Homolya I; Brain Imaging Centre, Research Centre for Natural Sciences, Budapest, Hungary., Oberberger J; Department of Internal Medicine I, University Hospital Würzburg, Würzburg, Germany., Jakob PM; Department of Physics, University of Würzburg, Würzburg, Germany., Blaimer M; Magnetic Resonance and X-ray Imaging Department, Fraunhofer Institute for Integrated Circuits IIS, Division Development Center X-Ray Technology, Würzburg, Germany.

Publikováno v: Magnetic resonance in medicine [Magn Reson Med] 2023 Feb; Vol. 89 (2), pp. 812-827. Date of Electronic Publication: 2022 Oct 13.

Towards fully automated inner ear analysis with deep-learning-based joint segmentation and landmark detection framework.

Autor: Stebani J; Magnetic Resonance and X-Ray Imaging Department, Fraunhofer Institute for Integrated Circuits IIS, 97074, Würzburg, Germany. jannik.stebani@iis.fraunhofer.de.; Universität Würzburg, Experimentelle Physik V, 97074, Würzburg, Germany. jannik.stebani@iis.fraunhofer.de.; Department of Oto-Rhino-Laryngology, Plastic, Aesthetic and Reconstructive Head and Neck Surgery and the Comprehensive Hearing Center, Universitätsklinikum Würzburg, 97080, Würzburg, Germany. jannik.stebani@iis.fraunhofer.de., Blaimer M; Magnetic Resonance and X-Ray Imaging Department, Fraunhofer Institute for Integrated Circuits IIS, 97074, Würzburg, Germany., Zabler S; Magnetic Resonance and X-Ray Imaging Department, Fraunhofer Institute for Integrated Circuits IIS, 97074, Würzburg, Germany.; Faculty of Computer Science, Deggendorf Institute of Technology, Deggendorf, Germany., Neun T; Institute for Diagnostic and Interventional Neuroradiology, Universitätsklinikum Würzburg, 97080, Würzburg, Germany., Pelt DM; Leiden Institute of Advanced Computer Science (LIACS), Universiteit Leiden, Leiden, CA, 2333, The Netherlands., Rak K; Department of Oto-Rhino-Laryngology, Plastic, Aesthetic and Reconstructive Head and Neck Surgery and the Comprehensive Hearing Center, Universitätsklinikum Würzburg, 97080, Würzburg, Germany.

Publikováno v: Scientific reports [Sci Rep] 2023 Nov 04; Vol. 13 (1), pp. 19057. Date of Electronic Publication: 2023 Nov 04.

Full utilization of conjugate symmetry: Combining virtual conjugate coil reconstruction with partial Fourier imaging for g-factor reduction in accelerated MRI

Autor: Kettinger, A.O., Setsompop, K., Kannengiesser, S.A.R., Breuer, F.A., Vidnyanszky, Z., Blaimer, M.

Purpose: In this study we propose a method to combine the parallel virtual conjugate coil (VCC) reconstruction with partial Fourier (PF) acquisition to improve reconstruction conditioning and reduce noise amplification in accelerated MRI where PF is

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______610::97e457acce55c2294540791348cec857
https://publica.fraunhofer.de/handle/publica/259444

Fast isotropic banding-free bSSFP imaging using 3D dynamically phase-cycled radial bSSFP (3D DYPR-SSFP) [Schnelle isotrope bandingfreie bSSFP Bildgebung mit 3D dynamisch phasenzykliertem radialem bSSFP (3D DYPR-SSFP)]

Autor: Benkert, T., Ehses, P., Blaimer, M., Jakob, P., Breuer, F.

Publikováno v: Zeitschrift für Medizinische Physik

Aims Dynamically phase-cycled radial balanced steady-state free precession (DYPR-SSFP) is a method for efficient banding artifact removal in bSSFP imaging. Based on a varying radiofrequency (RF) phase-increment in combination with a radial trajectory

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______1874::83f8289e7e28e78af351b2d90935127a
https://hdl.handle.net/21.11116/0000-0000-7A02-5