- Segmented the microscopic images of corneal endothelium cells and labeled each pixel as cell interior, cell border, or background.
- Developed and trained a 32x32 image patch-segmenting 24-layer U-Net model to an accuracy of 80% in training and 72% in validation.
- Reconstructed test segments by applying a sliding window operation on 500x500 test images while employing a 32x32 U-Net model.
- Plotted the ROC Curves and got an area under the curve (AUC) of 0.869 with the training set patches and 0.839 with the testing set patches.
NOTE: Open Final_Project.ipynb to see the full training, testing & evaluation processes.
