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Deep learning model automates radiotherapy treatment planning

By PulseAugur Editorial · [1 sources] ·

Researchers have developed Dose-PlanNet, a deep learning model designed to automate the complex process of prostate radiotherapy treatment planning. This physics-guided 3D architecture predicts dose distributions and was evaluated on patients undergoing two different fractionation regimens. While achieving comparable target coverage, Dose-PlanNet demonstrated statistically significant improvements in sparing organs at risk and met clinical acceptance criteria for a majority of automated plans across both treatment arms. AI

RANK_REASON The cluster contains a research paper published on arXiv detailing a new deep learning model for a specific scientific application. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Deep learning model automates radiotherapy treatment planning

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The cluster contains a research paper published on arXiv detailing a new deep learning model for a specific scientific application. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Ankit Bhattacharjee, Sougata Maity, Santam Chakraborty, Indranil Mallick ·

    Dose-PlanNet: Physics Based Radiotherapy Dose Prediction with Deep Learning

    arXiv:2608.26901v1 Announce Type: cross Abstract: Automating prostate radiotherapy treatment planning is dosimetrically complex, particularly for extreme hypofractionated regimens. In this study, we introduce Dose-PlanNet, a physics-guided 3D deep learning architecture designed t…

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