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ANHIR_MW

imported

software/anhir-mw

Software used by the AGH team during the ANHIR challenge.

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

ANHIR_MW project image
GitHub preview card for MWod/ANHIR_MW. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
Apache-2.0(osi)
Status
dormant
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
anhir · histology · image-registration · microscopy
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.

  • DeepHistReganhir · histology · image-registration · microscopy

    Code used to create the DeepHistReg submission to the ANHIR challenge.

  • MMIRhistology · image-registration · microscopy

    MMIR: Multimodal Image Registration

  • axondeepseghistology · microscopy

    Axon/Myelin segmentation using Deep Learning

  • sitk-ibeximage-registration · microscopy

    Aligning images acquired with the IBEX microscopy imaging technique

  • TemplateMatchingPyimage-registration · microscopy

    Python implementation of the Template Matching plugin from Fiji/ImageJ

  • ICIAR2018histology

    Two-Stage Convolutional Neural Network for Breast Cancer Histology Image Classification. ICIAR 2018 Grand Challenge on BreAst Cancer Histology images (BACH)

sources
  1. api.github.com/repos/MWod/ANHIR_MW
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2020-12-14, 28 stars, license reported as Apache-2.0. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/36.json→ .entries["anhir-mw"]

Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.