Efficient and robust 3D blind harmonization for large domain gaps | Paper Citation Record

Observation 0204905a-2f5c-4e09-b7ab-4043b78fca73 · outbound

This paper cites Understanding Hallucinations in Diffusion Models through Mode Interpolation.

Efficient and robust 3D blind harmonization for large domain gaps Understanding Hallucinations in Diffusion Models through Mode Interpolation

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This paper cites Deep learning for brain mri segmentation: state of the art and future directions.

Efficient and robust 3D blind harmonization for large domain gaps Deep learning for brain mri segmentation: state of the art and future directions

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This paper cites Auto- mated classification of alzheimer’s disease and mild cogni- tive impairment using a single mri and deep neural networks.

Efficient and robust 3D blind harmonization for large domain gaps Auto- mated classification of alzheimer’s disease and mild cogni- tive impairment using a single mri and deep neural networks

Reference 3

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This paper cites Deep gener- ative medical image harmonization for improving cross-site generalization in deep learning predictors.

Efficient and robust 3D blind harmonization for large domain gaps Deep gener- ative medical image harmonization for improving cross-site generalization in deep learning predictors

Reference 4

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This paper cites Har- monizing flows: Leveraging normalizing flows for unsuper- vised and source-free mri harmonization.

Efficient and robust 3D blind harmonization for large domain gaps Har- monizing flows: Leveraging normalizing flows for unsuper- vised and source-free mri harmonization

Reference 5

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This paper cites Memory-efficient 3d de- noising diffusion models for medical image processing.

Efficient and robust 3D blind harmonization for large domain gaps Memory-efficient 3d de- noising diffusion models for medical image processing

Reference 6

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This paper cites Imunity: a generalizable vae-gan solu- tion for multicenter mr image harmonization.Medical Image Analysis, 88:102799, 2023.

Efficient and robust 3D blind harmonization for large domain gaps Imunity: a generalizable vae-gan solu- tion for multicenter mr image harmonization.Medical Image Analysis, 88:102799, 2023

Reference 7

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This paper cites A computational approach to edge detection.

Efficient and robust 3D blind harmonization for large domain gaps A computational approach to edge detection

Reference 8

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This paper cites Contourdiff: Unpaired image translation with contourguided diffusion models.

Efficient and robust 3D blind harmonization for large domain gaps Contourdiff: Unpaired image translation with contourguided diffusion models

Reference 9

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This paper cites Solving 3d inverse problems us- ing pre-trained 2d diffusion models.

Efficient and robust 3D blind harmonization for large domain gaps Solving 3d inverse problems us- ing pre-trained 2d diffusion models

Reference 10

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This paper cites Predicting brain age with deep learn- ing from raw imaging data results in a reliable and heritable biomarker.

Efficient and robust 3D blind harmonization for large domain gaps Predicting brain age with deep learn- ing from raw imaging data results in a reliable and heritable biomarker

Reference 11

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Observation 468d13e7-8a41-4047-bf7f-e1cf3a8be648 · outbound

This paper cites Deepharmony: A deep learning approach to contrast harmonization across scanner changes.

Efficient and robust 3D blind harmonization for large domain gaps Deepharmony: A deep learning approach to contrast harmonization across scanner changes

Reference 12

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This paper cites A disentangled latent space for cross-site mri harmonization.

Efficient and robust 3D blind harmonization for large domain gaps A disentangled latent space for cross-site mri harmonization

Reference 13

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This paper cites Patched denoising diffusion models for high-resolution im- age synthesis.

Efficient and robust 3D blind harmonization for large domain gaps Patched denoising diffusion models for high-resolution im- age synthesis

Reference 14

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This paper cites Deep learning-based unlearning of dataset bias for mri harmonisation and confound removal.

Efficient and robust 3D blind harmonization for large domain gaps Deep learning-based unlearning of dataset bias for mri harmonisation and confound removal

Reference 15

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This paper cites Neural spline flows.

Efficient and robust 3D blind harmonization for large domain gaps Neural spline flows

Reference 16

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This paper cites Harmonization of multi-site diffusion tensor imaging data.

Efficient and robust 3D blind harmonization for large domain gaps Harmonization of multi-site diffusion tensor imaging data

Reference 17

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This paper cites Deep Generative Models for 3D Medical Image Synthesis.

Efficient and robust 3D blind harmonization for large domain gaps Deep Generative Models for 3D Medical Image Synthesis

Reference 18

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This paper cites Multi-site mri harmonization via attention-guided deep domain adaptation for brain dis- order identification.

Efficient and robust 3D blind harmonization for large domain gaps Multi-site mri harmonization via attention-guided deep domain adaptation for brain dis- order identification

Reference 19

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This paper cites Fast image-level mri harmonization via spec- trum analysis.

Efficient and robust 3D blind harmonization for large domain gaps Fast image-level mri harmonization via spec- trum analysis

Reference 20

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This paper cites Learning a variational network for reconstruction of accelerated mri data.

Efficient and robust 3D blind harmonization for large domain gaps Learning a variational network for reconstruction of accelerated mri data

Reference 21

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This paper cites Improved optimization for the robust and accurate linear registration and motion correction of brain images.

Efficient and robust 3D blind harmonization for large domain gaps Improved optimization for the robust and accurate linear registration and motion correction of brain images

Reference 22

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This paper cites Blindharmony:” blind” harmonization for mr images via flow model.

Efficient and robust 3D blind harmonization for large domain gaps Blindharmony:” blind” harmonization for mr images via flow model

Reference 23

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This paper cites Denoising diffusion probabilistic models for 3d medical image generation.

Efficient and robust 3D blind harmonization for large domain gaps Denoising diffusion probabilistic models for 3d medical image generation

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This paper cites Tackling structural hallucination in im- age translation with local diffusion.

Efficient and robust 3D blind harmonization for large domain gaps Tackling structural hallucination in im- age translation with local diffusion

Reference 25

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This paper cites Residual and plain convolutional neural networks for 3d brain mri classification.

Efficient and robust 3D blind harmonization for large domain gaps Residual and plain convolutional neural networks for 3d brain mri classification

Reference 26

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This paper cites Oasis-3: longitudinal neuroimaging, clin- ical, and cognitive dataset for normal aging and alzheimer disease.

Efficient and robust 3D blind harmonization for large domain gaps Oasis-3: longitudinal neuroimaging, clin- ical, and cognitive dataset for normal aging and alzheimer disease

Reference 27

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This paper cites Improving 3d imaging with pre-trained perpendicular 2d diffusion models.

Efficient and robust 3D blind harmonization for large domain gaps Improving 3d imaging with pre-trained perpendicular 2d diffusion models

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This paper cites Flow matching for generative modeling.

Efficient and robust 3D blind harmonization for large domain gaps Flow matching for generative modeling

Reference 29

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This paper cites Style transfer using generative adversarial networks for multi-site mri harmonization.

Efficient and robust 3D blind harmonization for large domain gaps Style transfer using generative adversarial networks for multi-site mri harmonization

Reference 30

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This paper cites Flow straight and fast: Learning to generate and transfer data with rectified flow.

Efficient and robust 3D blind harmonization for large domain gaps Flow straight and fast: Learning to generate and transfer data with rectified flow

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This paper cites Inter-site and inter-scanner diffusion mri data harmo- nization.

Efficient and robust 3D blind harmonization for large domain gaps Inter-site and inter-scanner diffusion mri data harmo- nization

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This paper cites Mri image harmonization using cycle- consistent generative adversarial network.

Efficient and robust 3D blind harmonization for large domain gaps Mri image harmonization using cycle- consistent generative adversarial network

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This paper cites Understanding SSIM.

Efficient and robust 3D blind harmonization for large domain gaps Understanding SSIM

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This paper cites On standardizing the mr image intensity scale.

Efficient and robust 3D blind harmonization for large domain gaps On standardizing the mr image intensity scale

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This paper cites New variants of a method of mri scale standardization.IEEE TMI, 19(2):143–150, 2000.

Efficient and robust 3D blind harmonization for large domain gaps New variants of a method of mri scale standardization.IEEE TMI, 19(2):143–150, 2000

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This paper cites On estimation of a probability density func- tion and mode.

Efficient and robust 3D blind harmonization for large domain gaps On estimation of a probability density func- tion and mode

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This paper cites Harmonization of large mri datasets for the anal- ysis of brain imaging patterns throughout the lifespan.

Efficient and robust 3D blind harmonization for large domain gaps Harmonization of large mri datasets for the anal- ysis of brain imaging patterns throughout the lifespan

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Observation f4cf67e9-cb62-44d9-8549-af05b0afa16b · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

Efficient and robust 3D blind harmonization for large domain gaps U-net: Convolutional networks for biomedical image segmentation

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This paper cites Progressive distillation for fast sampling of diffusion models.

Efficient and robust 3D blind harmonization for large domain gaps Progressive distillation for fast sampling of diffusion models

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This paper cites Machine learning on brain mri data for differential diagnosis of parkinson’s disease and pro- gressive supranuclear palsy.

Efficient and robust 3D blind harmonization for large domain gaps Machine learning on brain mri data for differential diagnosis of parkinson’s disease and pro- gressive supranuclear palsy

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This paper cites Statistical normalization techniques for magnetic resonance imaging.

Efficient and robust 3D blind harmonization for large domain gaps Statistical normalization techniques for magnetic resonance imaging

Reference 42

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This paper cites V olumet- ric analysis from a harmonized multisite brain mri study of a single subject with multiple sclerosis.

Efficient and robust 3D blind harmonization for large domain gaps V olumet- ric analysis from a harmonized multisite brain mri study of a single subject with multiple sclerosis

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This paper cites Fast robust automated brain extraction.

Efficient and robust 3D blind harmonization for large domain gaps Fast robust automated brain extraction

Reference 44

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This paper cites Diffusionblend: Learning 3d image prior through position-aware diffusion score blending for 3d com- puted tomography reconstruction.

Efficient and robust 3D blind harmonization for large domain gaps Diffusionblend: Learning 3d image prior through position-aware diffusion score blending for 3d com- puted tomography reconstruction

Reference 45

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This paper cites Consistency models.

Efficient and robust 3D blind harmonization for large domain gaps Consistency models

Reference 46

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This paper cites Mispel: A super- vised deep learning harmonization method for multi-scanner neuroimaging data.

Efficient and robust 3D blind harmonization for large domain gaps Mispel: A super- vised deep learning harmonization method for multi-scanner neuroimaging data

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:54:54.852818Z

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This paper cites Cannygan: Edge-preserving image trans- lation with disentangled features.

Efficient and robust 3D blind harmonization for large domain gaps Cannygan: Edge-preserving image trans- lation with disentangled features

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This paper cites Patch diffusion: Faster and more data- efficient training of diffusion models.

Efficient and robust 3D blind harmonization for large domain gaps Patch diffusion: Faster and more data- efficient training of diffusion models

Reference 49

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Observation da9f8300-8f3c-41b7-9434-c244869b4958 · outbound

This paper cites Quantitative sus- ceptibility mapping using deep neural network: Qsmnet.

Efficient and robust 3D blind harmonization for large domain gaps Quantitative sus- ceptibility mapping using deep neural network: Qsmnet

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:54:54.822324Z

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Observation a2566bfa-3cf7-4ed7-b714-ee50f39f3de0 · outbound

This paper cites Reliable source approximation: Source-free unsupervised domain adaptation for vestibular schwannoma mri segmentation.

Efficient and robust 3D blind harmonization for large domain gaps Reliable source approximation: Source-free unsupervised domain adaptation for vestibular schwannoma mri segmentation

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:54:54.812234Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 01b20e28-0784-49a5-81ea-687cb17f7ebf · outbound

This paper cites Seg- mentation of brain mr images through a hidden markov ran- dom field model and the expectation-maximization algo- rithm.

Efficient and robust 3D blind harmonization for large domain gaps Seg- mentation of brain mr images through a hidden markov ran- dom field model and the expectation-maximization algo- rithm

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:54:54.802807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation bca7efdd-f138-4bc2-a933-726d0bc2bf72 · outbound

This paper cites A deep learning model inte- grating fcnns and crfs for brain tumor segmentation.Medical Image Analysis, 43:98–111, 2018.

Efficient and robust 3D blind harmonization for large domain gaps A deep learning model inte- grating fcnns and crfs for brain tumor segmentation.Medical Image Analysis, 43:98–111, 2018

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:54:54.790875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 2bc5e559-d89b-422c-808e-110386b1fe59 · outbound

This paper cites Unpaired image-to-image translation using cycle- consistent adversarial networks.

Efficient and robust 3D blind harmonization for large domain gaps Unpaired image-to-image translation using cycle- consistent adversarial networks

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-16T04:54:54.648056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bfc4226a-b7c7-466e-af3b-724bf67f9013 · outbound

This paper cites Unsupervised mr harmonization by learning disentangled representations using information bottleneck theory.

Efficient and robust 3D blind harmonization for large domain gaps Unsupervised mr harmonization by learning disentangled representations using information bottleneck theory

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T04:54:54.775584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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