Research map / Label-efficient and robust learning / Domain adaptation and generalization

Cross-modality medical segmentation adaptation

Adapts medical segmentation across imaging modalities using frequency and volumetric alignment.

20 accepted papers at ICML, NeurIPS, ICLR, CVPR and AAAI (2019–2026) · an approach in Domain adaptation and generalization, keyword cluster “segmentation · semantic · domain adaptive”

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Where it stands

Not enough benchmark data Fewer than four papers report the same benchmark, so there is no record to follow.

5 papers in 2023–24 and 10 in 2025–26 (at ICML, NeurIPS, ICLR, CVPR and AAAI); its share of the topic grew, from 1.5% to 3.1%.

How this is decided

A benchmark is tracked when at least four papers of this approach report their own method on the same dataset and metric in at least two different years. Its record is the best number reported up to 2024 compared with the best reported in 2025–26: still improving means at least 1% better, flat means at most 0.2% better with at least two papers from 2025–26 trying. Numbers on a different scale from the rest (a fraction among percentages) and far outliers are left out. Results come from different papers with different setups, so they are signals, not head-to-head comparisons. The share of papers is counted at ICML, NeurIPS, ICLR, CVPR and AAAI.

How it got here

Most cited paper of each year

2019 · Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation (AAAI 2019 · 334 citations)
2020 · What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation (CVPR 2020 · 146 citations)
2021 · Minimizing Labeling Cost for Nuclei Instance Segmentation and Classification with Cross-domain Images and Weak Labels (AAAI 2021 · 16 citations)
2022 · Generalizable Cross-Modality Medical Image Segmentation via Style Augmentation and Dual Normalization (CVPR 2022 · 102 citations)
2023 · SDC-UDA: Volumetric Unsupervised Domain Adaptation Framework for Slice-Direction Continuous Cross-Modality Medical Image Segmentation (CVPR 2023 · 49 citations)
2024 · MAPSeg: Unified Unsupervised Domain Adaptation for Heterogeneous Medical Image Segmentation Based on 3D Masked Autoencoding and Pseudo-Labeling (CVPR 2024 · 35 citations)
2025 · AIF-SFDA: Autonomous Information Filter Driven Source-Free Domain Adaptation for Medical Image Segmentation (AAAI 2025 · 18 citations)
2026 · Knowledge Transfer Scaling Laws for 3D Medical Imaging (NeurIPS 2026 · 0 citations)

Earliest papers here

Synergistic Image and Feature Adaptation: Towards Cross-Modality Domain Adaptation for Medical Image Segmentation (AAAI 2019 · 334 citations)
What Can Be Transferred: Unsupervised Domain Adaptation for Endoscopic Lesions Segmentation (CVPR 2020 · 146 citations)
Unsupervised Instance Segmentation in Microscopy Images via Panoptic Domain Adaptation and Task Re-Weighting (CVPR 2020 · 76 citations)

What has been tried

14 papers here report 156 measured changes (a component added, removed or swapped, compared with a baseline): helped 78%, no clear effect 1%, hurt 15%, mixed 5%. Papers mostly publish changes that helped, so "helped" is over-represented.

Ablations in recent papers

What was changed	Measured on	Result	Effect	Paper
Add MAE pretraining to MPL	Brain MRI cross-sequence · Dice (%)	39.5 -> 75.3	Helped	MAPSeg: Unified Unsupervised Domain Adaptation for Heterogeneous Medical Image Segmentation Based on 3D Masked Autoencoding and Pseudo-Labeling (CVPR 2024 · 35 citations)
add MI minimization	AVRDB · DSC	58.62 -> 62.34	Helped	AIF-SFDA: Autonomous Information Filter Driven Source-Free Domain Adaptation for Medical Image Segmentation (AAAI 2025 · 18 citations)
add reliable prototype pseudo-labels	VNC III → Lucchi (Subset1) · IoU(%)	71.8 -> 72.9	Helped	Alleviate and Mining: Rethinking Unsupervised Domain Adaptation for Mitochondria Segmentation from Pseudo-Label Perspective (AAAI 2025 · 5 citations)
Add NGM	Poly-GA (source: 1bxn, 1f1b, 1yg6) · mIoU	41.9 → 50.3	Helped	Vox-UDA: Voxel-wise Unsupervised Domain Adaptation for Cryo-Electron Subtomogram Segmentation with Denoised Pseudo-Labeling (AAAI 2025 · 2 citations)
Add Progressive Style Transfer (PST)	MSKT: T1c→FS T2W · average DSC (%)	66.71 -> 81.34	Helped	One-to-Multiple: A Progressive Style Transfer Unsupervised Domain-Adaptive Framework for Kidney Tumor Segmentation (NeurIPS 2024 · 2 citations)
add a vanilla VNet decoder	MMWHS CT to MR · Dice	60.6 -> 65.4	Helped	A Unified Degradation-Robust Approach to SSL and UDA for 3D Medical Images (AAAI 2025 · 1 citation)

What reviewers will expect

Datasets and baselines named in the 7 papers of this approach from 2025–2026 that have a full-text summary. Leaving out the common ones is a frequent review question.

Baselines

DANN · 2 of 7 papers

Recent preprints

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Use it

Download BibTeX of 20 key papers Open the topic in the interactive map

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Same keyword cluster

Adaptation for semantic segmentation (81 papers)
Domain-generalized segmentation (56 papers)

Elsewhere in the topic

Conditional distribution alignment (162 papers)
Cross-domain few-shot with transformers (116 papers)
Feature alignment for unsupervised adaptation (105 papers)
Optimization-based domain generalization (101 papers)
Adversarial domain adaptation (95 papers)
Geometric alignment and synthetic-to-real adaptation (93 papers)
Source-free domain adaptation (92 papers)
Statistical alignment and hypothesis testing (80 papers)

Benchmark numbers, ablations and baseline numbers are extracted by AI from each paper's full text and can be wrong; the paper is the authority. Data: results index of 2026-11-02, citation counts from OpenAlex (2026-10-09).