Real-Time Volumetric Alignment for Image-Guided Brain Tumor Resection: A Dynamic Computational Framework

This paper details the development and validation of a novel computational framework to address critical brain tissue shifts encountered during image-guided neurosurgery for tumor resection. Utilizing Dynamic Data-Driven Non-Rigid Registration (NRR), this system integrates advanced distributed computing and machine learning paradigms to significantly enhance registration accuracy and speed. We present a robust methodology demonstrating the capability to deliver precise intra-operative image updates within demanding clinical timelines, thereby supporting more complete and safer tumor excisions. Key challenges inherent to real-time integration in the operating room are identified and discussed, providing foundational insights for future advancements in adaptive neurosurgical navigation.