Non‐convex IMRT treatment planning using deep inverse optimization

This study presents an effective and computationally efficient approach to IMRT treatment planning by approximating non-convex dose-volume constraints with second-order cone programming and DIO. The method enhances plan quality by improving dose homogeneity and OAR sparing while significantly accelerating optimization convergence, offering a practical solution for advanced radiation therapy planning.