5 papers
A Machine-to-Machine Knowledge-Guided LLM Agent for Generalizable Radiotherapy Treatment Planning
Md Mainul Abrar, Xun Jia, Yujie Chi
In this work, we propose a prototype machine-to-machine (M2M) knowledge-guided Large Language Model (LLM) framework for automated radiotherapy treatment planning. In the proposed p…
Extending gPET for Multi-Layer PET Simulation
Satzhan Sitmukhambetov, Junwei Du, Mingwu Jin +1
Depth-of-interaction (DOI) encoding is an effective strategy for reducing parallax error and preserving spatial resolution in positron emission tomography (PET), particularly in co…
Advancements in Monte Carlo simulations with gMicroMC: reactive species build-up promotes radical-radical reactions at Flash dose rates
Miguel Molina-Hernandez, Patricia Gonçalves, Yujie Chi +1
Ultra-high dose rate irradiations to water indicate an enhancement of radical-radical reactions, which could potentially correlate with the Flash effect. The purpose of this work w…
New Insights into Automatic Treatment Planning for Cancer Radiotherapy Using Explainable Artificial Intelligence
Md Mainul Abrar, Xun Jia, Yujie Chi
Objective: This study aims to uncover the opaque decision-making process of an artificial intelligence (AI) agent for automatic treatment planning. Approach: We examined a previous…
Actor Critic with Experience Replay-based automatic treatment planning for prostate cancer intensity modulated radiotherapy
Md Mainul Abrar, Parvat Sapkota, Damon Sprouts +2
Background: Real-time treatment planning in IMRT is challenging due to complex beam interactions. AI has improved automation, but existing models require large, high-quality datase…