This project focuses on developing a lightweight, automated segmentation model for kidney ultrasound images, addressing the limitations of manual extraction methods prone to inconsistencies. Leveraging the Open Kidney Ultrasound Dataset, our model significantly reduces computational demands while maintaining high performance, making it particularly suitable for resource-limited settings. By enhancing the efficiency and accessibility of kidney image analysis, this research aims to support improved diagnostics and patient care, especially in areas with limited medical resources.