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Robustness of breast lesion segmentation under MRI undersampling improves with k-space-aware deep learning
Purpose: To assess whether breast lesion segmentation can be learned directly from acquired MRI k-space, and whether doing so improves …
Lukas T. Rotkopf, Marco Schlimbach, Julius C. Holzschuh", Heinz-Peter Schlemmer, Jens Kleesiek, Moritz Rempe
May 21, 2026 arXiv
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Robustness of breast lesion segmentation under MRI undersampling improves with k-space-aware deep learning
Efficient Complex-Valued Vision Transformers for MRI Classification Directly from k-Space
Deep learning applications in Magnetic Resonance Imaging (MRI) predominantly operate on reconstructed magnitude images, a process that …
Moritz Rempe, Lukas T. Rotkopf, Marco Schlimbach, Helmut Becker, Fabian Hörst, Johannes Haubold, Philipp Dammann, Kevin Kröninger, Jens Kleesiek
Jan 26, 2026 arXiv
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Efficient Complex-Valued Vision Transformers for MRI Classification Directly from k-Space
Tumor likelihood estimation on MRI prostate data by utilizing k-Space information
We present a novel preprocessing and prediction pipeline for the classification of magnetic resonance imaging (MRI) that takes …
Moritz Rempe, Fabian Hörst, Constantin Seibold, Boris Hadaschik, Marco Schlimbach, Jan Egger, Kevin Kröninger, Felix Breuer, Martin Blaimer, Jens Kleesiek
Jun 4, 2024 ISMRM 2025
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Tumor likelihood estimation on MRI prostate data by utilizing k-Space information