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References from MSRepaint: Multiple Sclerosis Repaint with conditional denoising diffusion implicit model for bidirectional lesion filling and synthesis. Local targets link to admitted publications; unresolved targets remain external evidence.
MRI in multiple sclerosis: Current status and future prospects
10.1016/s1474-4422(08)70137-6 · 2008 · External reference
Voxelmorph: a learning framework for deformable medical image registration
10.1109/tmi.2019.2897538 · 2019 · External reference
Subject-specific lesion generation and pseudo-healthy synthesis for multiple sclerosis brain images
2022 · External reference
Evaluating and reducing the impact of white matter lesions on brain volume measurements
10.1002/hbm.21344 · 2012 · External reference
Spatial normalization of brain images with focal lesions using cost function masking
10.1006/nimg.2001.0845 · 2001 · External reference
Automated volumetric assessment with artificial neural networks might enable a more accurate assessment of disease burden in patients with multiple sclerosis
10.1007/s00330-019-06593-y · 2020 · External reference
Longitudinal multiple sclerosis lesion segmentation: Resource and challenge
10.1016/j.neuroimage.2016.12.064 · 2017 · External reference
Longitudinal multiple sclerosis lesion segmentation data resource
10.1016/j.dib.2017.04.004 · 2017 · External reference
Image harmonization improves consistency of intra-rater delineations of MS lesions in heterogeneous MRI
2024 · External reference
Reducing the impact of white matter lesions on automated measures of brain gray and white matter volumes
10.1002/jmri.22214 · 2010 · External reference
Encoder-only image registration
2026 · External reference
Beyond the LUMIR challenge: The pathway to foundational registration models
10.1016/j.media.2026.104175 · 2026 · External reference
Minimizing the effect of white matter lesions on deep learning based tissue segmentation for brain volumetry
10.1016/j.compmedimag.2022.102157 · 2023 · External reference
Unresolved reference
1997 · External reference
Objective evaluation of multiple sclerosis lesion segmentation using a data management and processing infrastructure
10.1038/s41598-018-31911-7 · 2018 · External reference
A self-adaptive network for multiple sclerosis lesion segmentation from multi-contrast MRI with various imaging sequences
2019 · External reference
FreeSurfer
10.1016/j.neuroimage.2012.01.021 · 2012 · External reference
10.1109/cvpr46437.2021.00294
10.1109/cvpr46437.2021.00294 · External reference
Generative adversarial nets
2014 · External reference
Non-local means inpainting of MS lesions in longitudinal image processing
10.3389/fnins.2015.00456 · 2015 · External reference
Repeatability and reproducibility of FreeSurfer, FSL-SIENAX and SPM brain volumetric measurements and the effect of lesion filling in multiple sclerosis
10.1007/s00330-018-5710-x · 2019 · External reference
The topograpy of demyelination and neurodegeneration in the multiple sclerosis brain
10.1093/brain/awv398 · 2016 · External reference
Fastsurfer-a fast and accurate deep learning based neuroimaging pipeline
10.1016/j.neuroimage.2020.117012 · 2020 · External reference
Denoising diffusion probabilistic models
2020 · External reference
Self-supervised brain lesion generation for effective data augmentation of medical images
10.1016/j.neunet.2025.107629 · 2025 · External reference
3D whole brain segmentation using spatially localized atlas network tiles
10.1016/j.neuroimage.2019.03.041 · 2019 · External reference
SynthSR: A public AI tool to turn heterogeneous clinical brain scans into high-resolution T1-weighted images for 3D morphometry
10.1126/sciadv.add3607 · 2023 · External reference
10.1038/s41592-020-01008-z · 2021 · Admitted local publication
FSL
10.1016/j.neuroimage.2011.09.015 · 2012 · External reference
A novel public MR image dataset of multiple sclerosis patients with lesion segmentations based on multi-rater consensus
10.1007/s12021-017-9348-7 · 2018 · External reference
10.1109/cvpr52688.2022.01117
10.1109/cvpr52688.2022.01117 · External reference
White matter lesion filling improves the accuracy of cortical thickness measurements in multiple sclerosis patients: a longitudinal study
10.1186/1471-2202-15-106 · 2014 · External reference
Long-MS-diff: Towards generating anatomically plausible lesion progression in MS imaging using diffusion models
2025 · External reference
Which training methods for GANs do actually converge?
2018 · External reference
The traditional versus early aggressive therapy for multiple sclerosis (TREAT-MS) trial: design and baseline characteristics of participants
10.1016/j.cct.2025.108117 · 2025 · External reference
Improved denoising diffusion probabilistic models
2021 · External reference
FastSurfer-LIT: Lesion inpainting tool for whole-brain MRI segmentation with tumors, cavities, and abnormalities
10.1162/imag_a_00446 · 2025 · External reference
A multi-time-point modality-agnostic patch-based method for lesion filling in multiple sclerosis
10.1016/j.neuroimage.2016.06.053 · 2016 · External reference
Unique MS lesion identification from MRI
2025 · External reference
Emerging perspectives on MRI application in multiple sclerosis: moving from pathophysiology to clinical practice
10.1148/radiol.221512 · 2023 · External reference
Current and future role of MRI in the diagnosis and prognosis of multiple sclerosis
2024 · External reference
U-net: Convolutional networks for biomedical image segmentation
2015 · External reference
Multiple sclerosis lesion synthesis in MRI using an encoder-decoder U-NET
10.1109/access.2019.2900198 · 2019 · External reference
Nonrigid registration of multiple sclerosis brain images using lesion inpainting for morphometry or lesion mapping
10.1002/hbm.20566 · 2009 · External reference
Reconstruction of the human cerebral cortex robust to white matter lesions: Method and validation
10.1002/hbm.22409 · 2014 · External reference
Denoising diffusion implicit models
2021 · External reference
LG-Net: Lesion gate network for multiple sclerosis lesion inpainting
2021 · External reference
LST-AI: A deep learning ensemble for accurate MS lesion segmentation
2024 · External reference
TumorCP: A simple but effective object-level data augmentation for tumor segmentation
2021 · External reference
Robust multiple sclerosis lesion inpainting with edge prior
2020 · External reference
CarveMix: A simple data augmentation method for brain lesion segmentation
10.1016/j.neuroimage.2023.120041 · 2023 · External reference
Unresolved reference
External reference
Unresolved reference
External reference
UNISELF: A unified network with instance normalization and self-ensembled lesion fusion for multiple sclerosis lesion segmentation
2026 · External reference
Towards an accurate and generalizable multiple sclerosis lesion segmentation model using self-ensembled lesion fusion
2024 · External reference
Bi-directional MS lesion filling and synthesis using denoising diffusion implicit model-based lesion repainting
2025 · External reference
Towards an accurate and generalizable multiple sclerosis lesion segmentation model using self-ensembled lesion fusion
2024 · External reference
HACA3: A unified approach for multi-site MR image harmonization
10.1016/j.compmedimag.2023.102285 · 2023 · External reference
