We have provided details of Fast U-Net model for medical image segmentation task. The saved model and it's weights are provided. To test the model you need just to run the test.py code. Please note that you need to set-up the dependencies to run the code.
In the Dataset folder, We have provided Abdominal Circumference (AC), and Head Circumference (HC) data to train and test the model. To have sufficient train, you must combine all image files (image1, image2, or image3) in a single image folder. moreover, train and validation sets are listed in .txt Docs for both HC and AC.
Important note: if you use these datasets, Cite our paper entitled "Fast and Accurate U-Net Model for Medical Image Segmentation".