AI Model for Head and Neck Autoplanning - Kujtim Latifi - RaySearch Webinars ASTRO 2025 Edition

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This video presents a research-driven approach to automating head and neck radiotherapy planning using deep learning, featuring insights from Kritim Latifi at Moffitt Cancer Center. The discussion covers the clinic's stringent dose requirements, challenges with traditional auto-planning tools, and the development of a deep learning model that produces clinically acceptable plans in under 30 minutes. Results show promising performance, especially for smaller targets, with ongoing work to improve robustness and fully automate adaptive workflows for head and neck cases.
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Oncology
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