MoFD: Synthetic Contrast-Enhanced Brain MRI From T1, T2 and FLAIR
MoFD predicts a contrast-enhanced T1 brain MRI from non-contrast T1, T2 and FLAIR with a 3D U-Net that mixes sequence features and their differences. arXiv:2610.21703.
DeBoneDiT: Soft-Tissue Chest X-Rays Without Dual-Energy Hardware
DeBoneDiT turns one standard PA chest X-ray into a dual-energy style soft-tissue image in about 3.4 seconds. Apache-2.0 code and weights, arXiv:2610.19466.
AD-GS: Sharper Dental CBCT From Fewer Projections
AD-GS fits each dental CBCT scan with 3D Gaussians, steering them toward enamel and bone so 20 to 30 projections keep root and crown edges. arXiv:2610.14963, BMVC 2026.
PSMAReg: Follow-Up PET/CT Registration That Keeps Tumor Burden
A LapIRN pipeline from Helmholtz Munich and TUM aligns follow-up PSMA PET/CT to baseline while holding MTV and TLG steady. arXiv:2610.21451, MIT code and weights.
MMA-LTS: Trust Tumor Overlay Confidence When MRI Sequences Are Missing
MMA-LTS (arXiv:2610.11419) post-hoc calibrates voxel-wise tumor overlay confidence when MRI sequences are missing, cutting ECE while keeping Dice. KAIST. No public code yet.
MID: Score Segmentation Batches Without Per-Case Labels
MID (arXiv:2610.17354) scores a batch of predicted segmentations against a labeled reference without per-case GT pairing, via joint MedSigLIP embeddings and a Fréchet / W2^2 distance. Apache 2.0 code on GitHub.
TDBM: Vessel Maps from X-ray Coronary Angiography
TDBM, by Hao, Cantrell, Abdalla, Ansari and Zhou (arXiv:2610.14105), recovers contrast-preserving coronary vessels from X-ray angiography sequences with a temporal diffusion bridge trained on physics-informed synthetic data, without manual vessel labels. Code is GPL-3.0 on GitHub with Google Drive checkpoints.
BrainNet: Cortical Surfaces from Any Brain MRI
BrainNet, by Nielsen, Gopinath, Hoopes, Dalca, Thielscher, Iglesias and Puonti (arXiv:2610.16595), reconstructs WM and GM cortical surfaces with vertex-wise uncertainty and fsaverage spherical registration from heterogeneous brain MRI, including thick-slice clinical FLAIR. Inference is about 0.6 s on GPU. Code is GPL-3.0 on GitHub with three TopoFit weight variants.
ribline: Numbered 3D Rib Centerlines from Thoracic CT
ribline, by Quan Wang (arXiv:2610.16047), traces and numbers all 24 rib centerlines (R01 to R12, L01 to L12) in thoracic CT with a hybrid Semantic Context Forest plus 3D U-Net detector and bilateral Viterbi matching. On the SCR 2 mm benchmark it reports LCD 2.05 mm and 97.2% labeling accuracy on 12 evaluation scans, with honest caveats on Stage-3 tuning and a 5-fold CV at 3.64 mm / 91.8%. Code is MIT on GitHub and PyPI; weights are on Hugging Face.
CIRSeg: Liver MRI Masks That Survive Scanner Shift
CIRSeg (Xu, Gao, Luo, Chen) is a cascaded nnU-Netv2 liver segmenter for CARE 2026 contrast-enhanced MRI. It trains with 3D CutMix and Nyul or histogram intensity transfer, refines a coarse prior at full resolution, can adapt at test time without source data, and drops disconnected false positives with LCC filtering. Official CARE eval: Dice 0.9713, HD95 18.31 mm; OOD test 0.9797 / 11.36. Claimed GitHub URL returned HTTP 404 on 13 October 2026. arXiv:2610.09784.