Organs at Risk

Machine learning based radiomics model to predict radiotherapy induced cardiotoxicity in breast cancer.

Journal of applied clinical medical physics 39704607

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...

Adult Aged Breast Neoplasms Cardiotoxicity Echocardiography Female Humans Machine Learning Middle Aged Organs at Risk Radiation Injuries Radiomics Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted Radiotherapy, Intensity-Modulated Unilateral Breast Neoplasms

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Automatic plan selection using deep network-A prostate study.

Medical physics 39657031

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...

Algorithms Automation Brachytherapy Deep Learning Humans Male Organs at Risk Prostatic Neoplasms Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted

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[Application of artificial intelligence-based organ contouring software and comparison of results in treatment planning for radiotherapy].

Orvosi hetilap 39645642

Algorithms Artificial Intelligence Humans Neoplasms Organs at Risk Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted Software Tomography, X-Ray Computed

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An assessment of the influence of trade-off optimization in commercial knowledge based planning library creation for tongue cancer patients.

Medical dosimetry : official journal of the American Association of Medical Dosimetrists 39645424

This article aims to compare the dosimetric performance between knowledge-based plan (KBP) libraries with and without trade-off (TO) exploration using multicriterial optimization (MCO) for tongue cancer patients. The trade-off optimized library (KBP_...

Humans Knowledge Bases Organs at Risk Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted Tongue Neoplasms

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Estimation of heart dose in left breast cancer radiotherapy: Assessment of vDIBH feasibility using the supervised machine learning algorithm.

Journal of applied clinical medical physics 39641663

BACKGROUND AND OBJECTIVE: The volunteer deep inspiration breath hold (vDIBH) technique is used to reduce the heart dose in left breast cancer radiotherapy. Many times, it is faced that despite rigorous exercise and training, not all patients get bene...

Adult Algorithms Breast Neoplasms Breath Holding Feasibility Studies Female Heart Humans Middle Aged Organs at Risk Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted Radiotherapy, Intensity-Modulated Supervised Machine Learning Unilateral Breast Neoplasms

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Assessing population-based to personalized planning strategies for head and neck adaptive radiotherapy.

Journal of applied clinical medical physics 39626092

PURPOSE: Optimal head-and-neck cancer (HNC) treatment planning requires accurate and feasible planning goals to meet dosimetric constraints and generate robust online adaptive treatment plans. A new x-ray-based adaptive radiotherapy (ART) treatment p...

Algorithms Artificial Intelligence Head and Neck Neoplasms Humans Organs at Risk Precision Medicine Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted Radiotherapy, Intensity-Modulated Retrospective Studies

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Under-representation for Female Pelvis Cancers in Commercial Auto-segmentation Solutions and Open-source Imaging Datasets.

Clinical oncology (Royal College of Radiologists (Great Britain)) 39837727

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...

Algorithms Artificial Intelligence Female Humans Male Organs at Risk Pelvic Neoplasms Radiotherapy Planning, Computer-Assisted

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Evaluation of AI-based auto-contouring tools in radiotherapy: A single-institution study.

Journal of applied clinical medical physics 39837647

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...

Algorithms Artificial Intelligence Humans Image Processing, Computer-Assisted Neoplasms Organs at Risk Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted Radiotherapy, Intensity-Modulated Software

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Automatic segmentation of MRI images for brain radiotherapy planning using deep ensemble learning.

Biomedical physics & engineering express 39831736

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 ...

Algorithms Brain Brain Neoplasms Deep Learning Ensemble Learning Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Neural Networks, Computer Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy, Image-Guided

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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) 39778325

PURPOSE: To investigate the performance of a machine learning-based segmentation method for treatment planning of gastric cancer.

Automation Humans Image Processing, Computer-Assisted Machine Learning Organs at Risk Radiometry Radiotherapy Dosage Radiotherapy Planning, Computer-Assisted Radiotherapy, Intensity-Modulated Stomach Neoplasms Tomography, X-Ray Computed

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AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Machine learning based radiomics model to predict radiotherapy induced cardiotoxicity in breast cancer.

Automatic plan selection using deep network-A prostate study.

[Application of artificial intelligence-based organ contouring software and comparison of results in treatment planning for radiotherapy].

An assessment of the influence of trade-off optimization in commercial knowledge based planning library creation for tongue cancer patients.

Estimation of heart dose in left breast cancer radiotherapy: Assessment of vDIBH feasibility using the supervised machine learning algorithm.

Assessing population-based to personalized planning strategies for head and neck adaptive radiotherapy.

Under-representation for Female Pelvis Cancers in Commercial Auto-segmentation Solutions and Open-source Imaging Datasets.

Evaluation of AI-based auto-contouring tools in radiotherapy: A single-institution study.

Automatic segmentation of MRI images for brain radiotherapy planning using deep ensemble learning.

A qualitative, quantitative and dosimetric evaluation of a machine learning-based automatic segmentation method in treatment planning for gastric cancer.

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