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DAG4MIA

imported

software/dag4mia

Domain Adaptation and Generalization for Medical Image Analysis

Machine-generated from the listed sources and not yet reviewed by a human.

record
Category
Software & Systems
Subcategory
unknown
License
MIT(osi)
Status
dormant
Maturity
deployed
Organization
HiLab-git
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
domain-adaptation · domain-generalization · medical-imaging
Regulatory
unknown
built by · 2

Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.

similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

  • DCACdomain-adaptation · domain-generalization

    Code for [IEEE-TMI] Domain and Content Adaptive Convolution based Multi-Source Domain Generalization for Medical Image Segmentation.

  • SLAugdomain-adaptation · domain-generalization

    [AAAI 2023] Official PyTorch implementation of the paper "SLAug: Rethinking Data Augmentation for Single-source Domain Generalization in Medical Image Segmentation"

  • TRUSGlandSegmentationdomain-generalization · medical-imaging

    Domain Generalization for Prostate Segmentation in Transrectal Ultrasound Images: A Multi-center Study

  • domainadaptationdomain-adaptation · medical-imaging

    Repository for the article "Unsupervised domain adaptation for medical imaging segmentation with self-ensembling".

  • On-The-Fly-Adaptationdomain-adaptation · medical-imaging

    Code base for "On-the-Fly Test-time Adaptation for Medical Image Segmentation"

  • Dual-Normalizationdomain-generalization

    [CVPR‘22] Generalizable Cross-modality Medical Image Segmentation via Style Augmentation and Dual Normalization

sources
  1. api.github.com/repos/HiLab-git/DAG4MIA
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2024-03-24, 150 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.

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machine-readable

/v1/entries/22.json→ .entries["dag4mia"]

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