3 papers
cs.CV2026
Efficient Complex-Valued Vision Transformers for MRI Classification Directly from k-Space
Moritz Rempe, Lukas T. Rotkopf, Marco Schlimbach +6
Deep learning applications in Magnetic Resonance Imaging (MRI) predominantly operate on reconstructed magnitude images, a process that discards phase information and requires compu…
eess.IV2025
PhaseGen: A Diffusion-Based Approach for Complex-Valued MRI Data Generation
Moritz Rempe, Fabian Hörst, Helmut Becker +4
Magnetic resonance imaging (MRI) raw data, or k-Space data, is complex-valued, containing both magnitude and phase information. However, clinical and existing Artificial Intelligen…
cs.CV2025
CellViT++: Energy-Efficient and Adaptive Cell Segmentation and Classification Using Foundation Models
Fabian Hörst, Moritz Rempe, Helmut Becker +3
Digital Pathology is a cornerstone in the diagnosis and treatment of diseases. A key task in this field is the identification and segmentation of cells in hematoxylin and eosin-sta…