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nitrain

imported

software/nitrain

Train AI models efficiently on medical images using any framework

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

nitrain project image
GitHub preview card for nitrain/nitrain. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
AGPL-3.0(osi)
Status
dormant
Maturity
deployed
Organization
nitrain
Country
unknown
Homepage
unknown
Documentation
unknown
Tags
deep-learning · keras · medical-imaging · neuroimaging · pytorch
Regulatory
unknown
built by · 1

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.

  • Brain-tumor-classifierkeras · medical-imaging · neuroimaging

    Brain tumor classification model from MRI scans using a Convolutional Neural Newtwork (CNN) built with Tensor flow/Keras.

  • clinicadlmedical-imaging · neuroimaging · pytorch

    Open-source Python library for reproducible deep learning in neuroimaging

  • mindGlidemedical-imaging · neuroimaging · pytorch

    Brain MRI segmentation for multiple sclerosis — any sequence, any quality. pip install mindglide

  • niftiaimedical-imaging · neuroimaging · pytorch

    Train neural nets on 3D images (e.g. MRIs) 🧠

  • AMBERkeras · pytorch

    Automated Modelling for Biological Evidence-based Research

  • ProjectAiAikeras · pytorch

    AiAi.care project is teaching computers to "see" chest X-rays and interpret them how a human Radiologist would. We are using 700,000 Chest X-Rays + Deep Learning to build an FDA 💊 approved,…

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

    Machine-imported from GitHub search. Last push 2024-06-13, 1880 stars, license reported as AGPL-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/42.json→ .entries["nitrain"]

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