Technology in cancer research & treatment
40152005
The aim was to evaluate a deep learning-based auto-segmentation method for liver delineation in Y-90 selective internal radiation therapy (SIRT). A deep learning (DL)-based liver segmentation model using the U-Net3D architecture was built. Auto-segme...
This study developed and evaluated an automatic segmentation model based on the Mamba framework (AM-UNet) for rapid and precise delineation of high-risk clinical target volume (HRCTV) and organs at risk (OARs) in cervical cancer brachytherapy. Using ...
Clinical oncology (Royal College of Radiologists (Great Britain))
40120536
AIMS: To assess geometric accuracy and dosimetric impact of a deep learning segmentation (DLS) model on a large, diverse dataset of head and neck cancer (HNC) patients treated with intensity-modulated proton therapy (IMPT).
Journal of applied clinical medical physics
40108745
PURPOSE: Balancing quality and efficiency has been a challenge for online adaptive therapy. Most systems start the online re-optimization with the original planning goals. While some systems allow planners to modify the planning goals, achieving a hi...
INTRODUCTION: Nasopharyngeal carcinoma (NPC) typically presents as advanced disease due to the lack of significant symptoms in the early stages. Accurate prognostication is therefore challenging as current methods based on anatomical staging often la...
An MRI-only workflow requires synthetic computed tomography (sCT) images to enable dose calculation. This study evaluated the dosimetric and patient positioning accuracy of deep learning-generated sCT for liver radiotherapy.sCT images were generated ...
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
40174514
PURPOSE: The generalization ability of deep learning-based automatic segmentation techniques for lung cancer in practical clinical applications remains under-validated. We reported an investigation that validated a robust semi-supervised conditional ...
This work aims to develop and investigate the feasibility of a hybrid model combining Monte Carlo (MC) simulations and deep learning (DL) to predict electronic portal imaging device (EPID) images based on MC-generated exit phase space energy fluence ...
. The dose distribution of lung cancer patients treated with the CyberKnife (CK) system is influenced by various factors, including tumor location and the direction of CK beams. The objective of this study is to present a deep learning approach that ...
Progress in biomedical engineering (Bristol, England)
40174629
Artificial intelligence (AI) incorporation into healthcare has proven revolutionary, especially in radiotherapy, where accuracy is critical. The purpose of the study is to present patterns and develop topics in the application of AI to improve the pr...