ArticleDomain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data : first MICCAI Workshop, DART 2019, and first International Workshop, MIL3ID 2019, Shenzhen, held in conjunction with MICCAI 20...2019
Multi-domain Adaptation in Brain MRI Through Paired Consistency and Adversarial Learning.
Article in Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data : first MICCAI Workshop, DART 2019, and first International Workshop, MIL3ID 2019, Shenzhen, held in conjunction with MICCAI 20..., 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
14 citing papers in PubMed.
- T-SCAPE: T cell immunogenicity scoring via cross-domain aided predictive engine.Science advances · 2025Article
- CLIP-Driven Universal Model for Organ Segmentation and Tumor Detection.Proceedings. IEEE International Conference on Computer Vision · 2023Article
- The Advent of Domain Adaptation into Artificial Intelligence for Gastrointestinal Endoscopy and Medical Imaging.Diagnostics (Basel, Switzerland) · 2023Review
- Machine Learning for Brain MRI Data Harmonisation: A Systematic Review.Bioengineering (Basel, Switzerland) · 2023Review
- Dual adversarial models with cross-coordination consistency constraint for domain adaption in brain tumor segmentation.Frontiers in neuroscience · 2023Article
- CrossMoDA 2021 challenge: Benchmark of cross-modality domain adaptation techniques for vestibular schwannoma and cochlea segmentation.Medical image analysis · 2023Article
- CellTranspose: Few-shot Domain Adaptation for Cellular Instance Segmentation.IEEE Winter Conference on Applications of Computer Vision. IEEE Winter Conference on Applications of Computer Vision · 2023Article
- Adaptation to CT Reconstruction Kernels by Enforcing Cross-Domain Feature Maps Consistency.Journal of imaging · 2022Article
- Domain Adaptation for Medical Image Analysis: A Survey.IEEE transactions on bio-medical engineering · 2022Review
- Transfer Learning in Magnetic Resonance Brain Imaging: A Systematic Review.Journal of imaging · 2021Review
- Harmonized Segmentation of Neonatal Brain MRI.Frontiers in neuroscience · 2021Article
- Deep Learning in Large and Multi-Site Structural Brain MR Imaging Datasets.Frontiers in neuroinformatics · 2021Review
- Learning joint segmentation of tissues and brain lesions from task-specific hetero-modal domain-shifted datasets.Medical image analysis · 2021Article
- Advancing Medical Imaging Informatics by Deep Learning-Based Domain Adaptation.Yearbook of medical informatics · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
Supervised learning algorithms trained on medical images will often fail to generalize across changes in acquisition parameters. Recent work in domain adaptation addresses this challenge and successfully leverages labeled data in a source domain to perform well on an unlabeled target domain. Inspired by recent work in semi-supervised learning we introduce a novel method to adapt from one source domain to
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.