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Purpose: In high-dose-rate (HDR) prostate brachytherapy procedures, the pattern of needle placement solely relies on physician experience. We investigated the feasibility of using reinforcement learning (RL) to provide needle positions and…

医学物理 · 物理学 2025-06-12 Tonghe Wang , Yining Feng , Xiaofeng Yang

Anatomical changes during intensity-modulated proton therapy (IMPT) for head-and-neck cancer (HNC) can shift Bragg peaks, risking tumor underdosing and organ-at-risk overdosing. Treatment replanning is often required to maintain clinically…

医学物理 · 物理学 2025-08-13 Malvern Madondo , Yuan Shao , Yingzi Liu , Jun Zhou , Xiaofeng Yang , Zhen Tian

Proton pencil beam scanning (PBS) treatment planning for head and neck (H&N) cancers is a time-consuming and experience-demanding task where a large number of planning objectives are involved. Deep reinforcement learning (DRL) has recently…

定量方法 · 定量生物学 2024-09-19 Qingqing Wang , Chang Chang

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 previously developed AI agent based on the Actor-Critic with…

医学物理 · 物理学 2025-08-21 Md Mainul Abrar , Xun Jia , Yujie Chi

High dose-rate brachytherapy (HDRBT) is widely used for gynecological cancer treatment. Although commercial treatment planning systems (TPSs) have inverse optimization modules, it takes several iterations to adjust planning objectives to…

医学物理 · 物理学 2021-09-14 Huan Liu , Chang M Ma , Xun Jia , Chenyang Shen , Peter Klages , Kevin Albuquerque

Most commercially available treatment planning systems for brachytherapy operate based on physical dose and do not incorporate fractionation or tissue-specific response. The purpose of this study is to investigate the potential for…

医学物理 · 物理学 2017-12-04 Kaelyn Seeley , I-Chow J. Hsu , Tae Min Hong , J. Adam Cunha

Inverse treatment planning in radiation therapy is formulated as optimization problems. The objective function and constraints consist of multiple terms designed for different clinical and practical considerations. Weighting factors of…

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 datasets and lack universal applicability. Deep reinforcement…

医学物理 · 物理学 2025-02-26 Md Mainul Abrar , Parvat Sapkota , Damon Sprouts , Xun Jia , Yujie Chi

To develop an automated workflow for rectal cancer three-dimensional conformal radiotherapy treatment planning that combines deep-learning(DL) aperture predictions and forward-planning algorithms. We designed an algorithm to automate the…

Head-and-neck cancer (HNC) planning is difficult because multiple critical organs-at-risk (OARs) are close to complex targets. Intensity-modulated carbon-ion therapy (IMCT) offers superior dose conformity and OAR sparing but remains slow…

Estimating over-amplification of human epidermal growth factor receptor 2 (HER2) on invasive breast cancer (BC) is regarded as a significant predictive and prognostic marker. We propose a novel deep reinforcement learning (DRL) based model…

计算机视觉与模式识别 · 计算机科学 2019-03-27 Talha Qaiser , Nasir M. Rajpoot

Radiotherapy (RT) is a critical cancer treatment, with volumetric modulated arc therapy (VMAT) being a commonly used technique that enhances dose conformity by dynamically adjusting multileaf collimator (MLC) positions and monitor units…

医学物理 · 物理学 2025-06-26 Stefanos Achlatis , Efstratios Gavves , Jan-Jakob Sonke

Objective: Radiotherapy treatment planning is a time-consuming and potentially subjective process that requires the iterative adjustment of model parameters to balance multiple conflicting objectives. Recent advancements in frontier…

Deep learning-based automated contouring and treatment planning has been proven to improve the efficiency and accuracy of radiotherapy. However, conventional radiotherapy treatment planning process has the automated contouring and treatment…

医学物理 · 物理学 2024-12-02 Sangwook Kim , Aly Khalifa , Thomas G. Purdie , Chris McIntosh

Deep learning has facilitated the automation of radiotherapy by predicting accurate dose distribution maps. However, existing methods fail to derive the desirable radiotherapy parameters that can be directly input into the treatment…

计算机视觉与模式识别 · 计算机科学 2024-03-01 Jiaqi Cui , Yuanyuan Xu , Jianghong Xiao , Yuchen Fei , Jiliu Zhou , Xingcheng Peng , Yan Wang

High-dose-rate brachytherapy is a tumor treatment method where a highly radioactive source is brought in close proximity to the tumor. In this paper we develop a simulated annealing algorithm to optimize the dwell times at preselected dwell…

医学物理 · 物理学 2017-03-29 Timo M. Deist , Bram L. Gorissen

In complex clinical decision-making, clinicians must often track a variety of competing metrics defined by aim (ideal) and limit (strict) thresholds. Sifting through these high-dimensional tradeoffs to infer the optimal patient-specific…

Immunohistochemistry (IHC) analysis is a well-accepted and widely used method for molecular subtyping, a procedure for prognosis and targeted therapy of breast carcinoma, the most common type of tumor affecting women. There are four…

图像与视频处理 · 电气工程与系统科学 2024-06-18 Sumit Kumar Jha , Purnendu Mishra , Shubham Mathur , Gursewak Singh , Rajiv Kumar , Kiran Aatre , Suraj Rengarajan

Purpose: Many planning methods for high dose rate (HDR) brachytherapy treatment planning require an iterative approach. A set of computational parameters are hypothesized that will give a dose plan that meets dosimetric criteria. A dose…

医学物理 · 物理学 2016-11-25 Timmy Siauw , Adam Cunha , Alper Atamturk , I-Chow Hsu , Jean Pouliot , Ken Goldberg

The development of a digital twin (DT) framework for fast online adaptive proton therapy planning in prostate stereotactic body radiation therapy (SBRT) with dominant intraprostatic lesion (DIL) boost represents a significant advancement in…

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