AIMC Topic: Organs at Risk
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Evaluation of AI-based auto-contouring tools in radiotherapy: A single-institution study.
Journal of applied clinical medical physics
Jan 21, 2025
BACKGROUND: Accurate delineation of organs at risk (OARs) is crucial yet time-consuming in the radiotherapy treatment planning workflow. Modern artificial intelligence (AI) technologies had made automation of OAR contouring feasible. This report deta...
Under-representation for Female Pelvis Cancers in Commercial Auto-segmentation Solutions and Open-source Imaging Datasets.
Clinical oncology (Royal College of Radiologists (Great Britain))
Jan 20, 2025
AIM: Artificial intelligence (AI) based auto-segmentation aids radiation therapy (RT) workflows and is being adopted in clinical environments facilitated by the increased availability of commercial solutions for organs at risk (OARs). In addition, op...
Automatic segmentation of MRI images for brain radiotherapy planning using deep ensemble learning.
Biomedical physics & engineering express
Jan 17, 2025
This study aimed to develop and evaluate an efficient method to automatically segment T1- and T2-weighted brain magnetic resonance imaging (MRI) images. We specifically compared the segmentation performance of individual convolutional neural network ...
A qualitative, quantitative and dosimetric evaluation of a machine learning-based automatic segmentation method in treatment planning for gastric cancer.
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)
Jan 7, 2025
PURPOSE: To investigate the performance of a machine learning-based segmentation method for treatment planning of gastric cancer.
Generalizability, robustness, and correction bias of segmentations of thoracic organs at risk in CT images.
European radiology
Dec 31, 2024
OBJECTIVE: This study aims to assess and compare two state-of-the-art deep learning approaches for segmenting four thoracic organs at risk (OAR)-the esophagus, trachea, heart, and aorta-in CT images in the context of radiotherapy planning.
Automated treatment planning with deep reinforcement learning for head-and-neck (HN) cancer intensity modulated radiation therapy (IMRT).
Physics in medicine and biology
Dec 24, 2024
To develop a deep reinforcement learning (DRL) agent to self-interact with the treatment planning system to automatically generate intensity modulated radiation therapy (IMRT) treatment plans for head-and-neck (HN) cancer with consistent organ-at-ris...
Machine learning based radiomics model to predict radiotherapy induced cardiotoxicity in breast cancer.
Journal of applied clinical medical physics
Dec 20, 2024
PURPOSE: Cardiotoxicity is one of the major concerns in breast cancer treatment, significantly affecting patient outcomes. To improve the likelihood of favorable outcomes for breast cancer survivors, it is essential to carefully balance the potential...
Artificial Intelligence-Empowered Multistep Integrated Radiation Therapy Workflow for Nasopharyngeal Carcinoma.
International journal of radiation oncology, biology, physics
Dec 19, 2024
PURPOSE: To establish an artificial intelligence (AI)-empowered multistep integrated (MSI) radiation therapy (RT) workflow for patients with nasopharyngeal carcinoma (NPC) and evaluate its feasibility and clinical performance.
Young Adult
Adult
Male
Middle Aged
Radiotherapy Planning, Computer-Assisted
Humans
Quality of Life
Tomography, X-Ray Computed
Artificial Intelligence
Radiotherapy, Intensity-Modulated
Workflow
Female
Prospective Studies
Nasopharyngeal Carcinoma
Feasibility Studies
Aged
Nasopharyngeal Neoplasms
Organs at Risk
Automatic plan selection using deep network-A prostate study.
Medical physics
Dec 10, 2024
BACKGROUND: Recently, high-dose-rate (HDR) brachytherapy treatment plans generation was improved with the development of multicriteria optimization (MCO) algorithms that can generate thousands of pareto optimal plans within seconds. This brings a shi...
[Application of artificial intelligence-based organ contouring software and comparison of results in treatment planning for radiotherapy].
Orvosi hetilap
Dec 8, 2024
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