Skip to main content

An Open-Source Python Toolkit for Automated Quantification of Corneal Nerve Fibers in Confocal Microscopy Images

Project description

description

English | 简体中文

SuperCCM Version 0.5.0

🚀 Introduction

✨️SuperCCM is an open-source Python framework for processing and analyzing corneal nerve images from corneal confocal microscopy (CCM). By providing a CCM corneal nerve image as input, SuperCCM can automatically process the image and output various clinically relevant morphological parameters. SuperCCM also allows fast and easy integration of independent algorithms (e.g., segmentation) into the framework.

🎆 Github: https://github.com/qlnfm/SuperCCM

🔮 Use Online

🤗 Hugging Face: https://huggingface.co/spaces/jugking6688/SuperCCM-Web

🏠 Our Website: http://aiccm.fun/

❇️ Environment Setup

conda create -n superccm python=3.10 -y
conda activate superccm
pip install -r requirements.txt
  • Install from PyPI:
pip install superccm

⚡ Quick Start

from superccm import DefaultWorkFlow

wf = DefaultWorkFlow()
metrics = wf.run('your/img/path')
print(metrics)

Or a simpler, less formal version:

from superccm.api import analysis

metrics = analysis('your/img/path')
print(metrics)

Or, enable Web service locally:

python app.py

📖 Documentation & Tutorials

SuperCCM follows a principle of simplicity, allowing users and developers to get started and master it with minimal cost and time.

  • ✨️ Quick Tutorial: Learn how to use SuperCCM in detail
  • ✨️ Module Development: Learn how to customize workflows and integrate your own algorithms into SuperCCM

📄 License

This project is licensed under the GPL v3 open-source license.

🎓 Academic Citation

coming soon ...

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

superccm-0.5.0.tar.gz (53.4 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

superccm-0.5.0-py3-none-any.whl (53.5 MB view details)

Uploaded Python 3

File details

Details for the file superccm-0.5.0.tar.gz.

File metadata

  • Download URL: superccm-0.5.0.tar.gz
  • Upload date:
  • Size: 53.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.18

File hashes

Hashes for superccm-0.5.0.tar.gz
Algorithm Hash digest
SHA256 f7f64e0f3c6bf423356ff5f9fd4bebb80000b13b78e4497a19401aa672b657cc
MD5 5ffde45371d90ae7955df77db33a1deb
BLAKE2b-256 b291520edbb7c84a8e66a1ef9c36232ee0ac16251de2bae7224524c7d4621097

See more details on using hashes here.

File details

Details for the file superccm-0.5.0-py3-none-any.whl.

File metadata

  • Download URL: superccm-0.5.0-py3-none-any.whl
  • Upload date:
  • Size: 53.5 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.10.18

File hashes

Hashes for superccm-0.5.0-py3-none-any.whl
Algorithm Hash digest
SHA256 f0e33934b425f5f430f0e58ec7728dea5b75bec1e9838af3c80deca685a57a8f
MD5 95a7ca0097b877c28d3014c300d82410
BLAKE2b-256 265f66e419330dd20f15fec282d9b7a8699677eaedb24f96a9d4be020950f22f

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page