arXiv Computer Vision
SliceBridge: context-consistent repair of corrupted slice intervals in T1-weighted MRI
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arXiv AI
Jun 30
Longitudinal Lesion Inpainting in Brain MRI via 3D Region Aware Diffusion
arXiv:2603. 05693v2 Announce Type: replace-cross Abstract: Accurate longitudinal analysis of brain MRI is often hindered by evolving lesions, which bias automated neuroimaging pipelines.
arXiv AI
Aug 10
Do 3D Medical Foundation Models See Through MRI Artifacts? A Controlled Study of Representation Robustness
arXiv:2608. 06613v1 Announce Type: cross Abstract: Self-supervised 3D medical foundation models are increasingly used as general-purpose feature extractors, yet their sensitivity to MRI artifacts remains poorly understood.
arXiv Computer Vision
2d ago
Conditional Flow Matching for Cross-Field MRI Harmonisation
arXiv:2609.00960v1 Announce Type: new Abstract: Magnetic resonance images of the same subject look markedly different across field strengths, which complicates the comparison and pooling of data acro...
arXiv Computer Vision
Aug 28
FLAT: FLow-Aligned Training of Unrolled Networks for MRI Reconstruction
FLAT: FLow-Aligned Training of Unrolled Networks for MRI Reconstruction proposes a new training method for unrolled neural networks used in MRI reconstruction. By interpreting unrolled networks as discretizations of conditional probability flows, the authors derive cascade parameters from Flow Matching and align intermediate reconstructions with the ideal Flow Matching trajectory. Experiments on three MRI datasets demonstrate that FLAT stabilizes the reconstruction trajectory across sub-networks and improves the final reconstruction quality.
arXiv Computer Vision
3d ago
CARD: Calibration via Agreement in Reverse Diffusion for Out-of-Domain MRI Segmentation
arXiv:2608.28681v1 Announce Type: new Abstract: Probability calibration aligns model confidence with predictive accuracy, enabling clinicians to identify unreliable segmentation regions. This alignme...
arXiv AI
Jul 23
PRIME-SVR: Physics-infoRmed Implicit Multi-Echo Slice-to-Volume Reconstruction for Fetal T2 mapping
arXiv:2607. 20136v1 Announce Type: cross Abstract: Slice-to-volume reconstruction (SVR) is the standard method for obtaining high-resolution (HR) 3D fetal brain volumes from motion-corrupted 2D MRI slice stacks acquired in multiple orientations.