3D U-Net to Leverage Spatial and Intensity Information from Different MRI Sequences to Enhance Tumor Boundary Delineation

Accurate tumor boundary delineation is critical in medical imaging for diagnosis, treatment planning, and outcome monitoring. This study presents a 3D U-Net architecture designed to leverage spatial and intensity information from multiple MRI sequences to improve tumor segmentation. By integrating data from different modalities, such as T1-weighted, T2-weighted, and FLAIR images, the network captures complementary features, enhancing its ability to differentiate between tumor tissue and surrounding structures.