Built a U-Net deep learning model for medical image segmentation of histopathological slides. The model performs pixel-wise classification to identify and segment cancerous tissue regions with high accuracy.

Implemented with TensorFlow and Keras using the U-Net architecture with skip connections for precise boundary detection. Evaluated with standard medical imaging metrics including Dice coefficient and IoU.