Enhancing liver tumor segmentation with UNet-ResNet: Leveraging ResNet's power.

Background: Liver cancer poses a significant health challenge due to its high incidence rates and complexities in detection and treatment. Accurate segmentation of liver tumors using medical imaging plays a crucial role in early diagnosis and treatment planning.

Objective: This study proposes a novel approach combining U-Net and ResNet architectures with the Adam optimizer and sigmoid activation function.