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

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title: SuperCCM Web Application emoji: 🚀 colorFrom: indigo colorTo: blue sdk: gradio sdk_version: "5.35.0" app_file: app.py pinned: false

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🚀 Introduction

✨️SuperCCM is an open-source Python framework for processing and analyzing corneal nerve images from corneal confocal microscopy (CCM). By inputting a CCM corneal nerve image, SuperCCM can automatically process the image and output various commonly used morphological parameters in clinical practice.

🌟 Using online

https://huggingface.co/spaces/jugking6688/SuperCCM

❇️ Environmental Preparation

conda create -n superccm python=3.10 -y
conda activate superccm
pip install -r requirements.txt

⚡ Quickly Start

from superccm import SuperCCM  # Import the superccm object from the SuperCCM package
import cv2

image = cv2.imread('path/to/your/image.png')  # Read the test image
# Of course, you can also obtain a picture object in any way you like
# Make sure the image is an np.ndarray object of shape (384, 384, 3) and type uint8
ccm = SuperCCM()  # Instantiate the SuperCCM object
metrics = ccm(image)  # Process and analyze the image, and return a dictionary storing various morphological parameters
print(metrics)  # Print parameters

📖 Document Tutorial

We offer a wealth of documentation and tutorials for users to delve deeply into SuperCCM. Click the link below to quickly jump to the corresponding section of the document.

📄 License

This project follows the GPL v3 open source license.

🎓 Academic Citation

coming soon ...

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