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STABLE

imported

software/stable

Preserving Spatial and Quantitative Information in Unpaired Biomedical Image-to-Image Translation

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

STABLE project image
GitHub preview card for NICALab/STABLE. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
GPL-3.0(osi)
Status
maintained
Maturity
deployed
Organization
NICALab
Country
unknown
Documentation
unknown
Tags
calcium-imaging · deep-learning · image-to-image-translation · microscopy · unsupervised-learning
Regulatory
unknown
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.

  • GutAnalysisToolboxcalcium-imaging · microscopy

    Analysis and characterisation of cells within the gut wall using deep learning models. The current focus is on studying enteric neurons and enteric glia.

  • miocalcium-imaging · microscopy

    miniscope I/O sdk

  • SUPPORTcalcium-imaging · microscopy

    Accurate denoising of voltage imaging data through statistically unbiased prediction, Nature Methods.

  • im2im-uqimage-to-image-translation · microscopy

    Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with rigorous, distribution-free uncertainty quantification.

  • Codes related to the paper "Attention-Based CNN-BiLSTM for Sleep States Classification of Spatiotemporal Wide-Field Calcium Imaging Data"

  • AutoStereotacalcium-imaging

    An open-source automated surgical instrument for microendoscope implantation

sources
  1. api.github.com/repos/NICALab/STABLE
    retrieved 2026-08-25 · via github-api

    Machine-imported from GitHub search. Last push 2025-10-14, 9 stars, license reported as GPL-3.0. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

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

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