Brain tumor segmentation is crucial in modern healthcare, playing a vital role in accurately diagnosing and treating brain-related illnesses. As medical imaging technology advances, it becomes increasingly important to identify and analyze brain tumors accurately. Segmentation enables medical professionals to discern intricate details of tumors, facilitating better treatment planning and execution. The purpose of this research is to identify the detailed process for the segmentation of brain tumors, intending to address the urgent health challenges facing the diverse population in Kansas. To improve the accuracy of brain tumor detection, especially for Kansas residents, we are working on improving the accuracy of the detection of brain tumors. Brain tumors pose a significant health challenge, so we are developing tools that can find them early. We are committed to improving the detection of brain tumors by using image-processing techniques and deep learning. We're using special magnetic resonance imaging (Brats MRI) to take really detailed pictures of the brain, and then we're using deep learning models to learn and identify brain tumors automatically. In other words, it would be like teaching a computer to be very good at spotting these types of threats. Kansans will benefit from this research since it aims to make sure we have better tools for detecting and treating brain tumors. The faster and more precise we can find tumors, the sooner people can receive the appropriate treatment, and that is good for the health of everyone. In order to improve healthcare in Kansas, especially for international students and all Kansas residents, we aim to share what we learn.