Please note that this repository has only been tested only on a Windows PC.

Clone the repository and machine learning model using the following command

git clone https://github.com/alvinkimbowa/clarius_model_integration.git

Install the necessary dependents, create a python environment and install the requirements using the commands below. Please note that this repository has only been tested with python environments.

python -m venv venv

cd venv/Scripts
activate
cd ../../

pip install -r requirements.txt

Run the inference_engine.py file, adjusting the data paths accordingly.

python inference_engine.py

• The current model was trained on 1787 images obtained with the GE LOGIQ P9 R3 ultrasound system with the L312-RS wideband linear array probe. However, the model can generalize to other devices, thanks to the contrast and intensity invariant Mono2D layer I integrated (See paper).

• The model achieves Dice of 95.56% on test images from GE LOGIQ P9 R3 images, and an average of 94.27% when evaluated with images from GE LOGIQe and Clarius L15 HD3.