Rafe A. McBeth, PhD

Automated treatment planning can reduce manual workload and improve consistency; however, supporting new clinical indications often requires development of dedicated tools rather than reuse of existing workflows. This study describes the creation of a central...

Current registration tools lack mechanisms for specifying clinical priorities. We developed a system accepting plain-text instructions (e.g., "prioritize tumor alignment for dose accumulation") and evaluated whether text guidance produces reliable, structure-...

To develop and validate an agentic AI framework using Model Context Protocol (MCP) that enables clinicians to control CT-MR image registration through natural language guidance. The study aims to determine if text-based clinical intent produces predictable, s...

Prostate cancer male reproductive system malignancy and the most common male cancer treated by radiation. Given the high incidence rate and complexities of treatment planning, artificial intelligence (AI) solutions in medical physics are essential to reducing...