An Open-Source Python Toolkit for Automated Quantification of Corneal Nerve Fibers in Confocal Microscopy Images
Project description
🚀 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.
❇️ 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.
- ✨️ Auto Analysis
- ✨️ Visualization
- ✨️ Bulk Analysis
- ✨️ Web Application
📄 License
This project follows the GPL v3 open source license.
🎓 Academic Citation
coming soon ...
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