Label-Free Quantification of Gold Nanoparticles using MC-CNN

Using Deep Learning to count the number of AuNPs in a live cell image.

Requirements and Setup

Python 3.9 and Pytorch 2.1.2+cu118 have been used.

See requirements.txt for other python libraries used.

To install, set up a virtual environment using pip. Then install required libraries using

pip install -r requirements.txt

Data

Please contact the authors for access to the data used for training the models.

Models

You can download the MC-CNN model here. If the link does not work, please contact the authors.

Count AuNPs

Put images for counting in a folder.

In scripts/asmm-cell-npns/infer.py, change the model path in Line 17 to where you saved the above model.

Then change the image path in Line 30 to the path to the folder where images to count are stored.

Finally, run the script

python scripts/asmm-cell-npns/infer.py run

To-Do

• Update this with a command line/argument based implementation for calling inference.
• Investigate PyImageJ and implement this as an ImageJ plugin if feasible.

Citation

If you use any of the code, trained models or data, please cite the paper.

Mohsin, A. S. M. and Choudhury, S. H. (2024). "A label free quantification of gold nanoparticle at the single cell level using multi-column convolutional neural network (MC-CNN)," The Analyst