AIMC Topic: Radiation Oncology
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Artificial intelligence based deconvolving on megavoltage photon beam profiles for radiotherapy applications.
Physics in medicine and biology
Mar 16, 2022
. The aim of this work is an AI based approach to reduce the volume effect of ionization chambers used to measure high energy photon beams in radiotherapy. In particular for profile measurements, the air-filled volume leads to an inaccurate measureme...
The 3 ESTRO-EFOMP core curriculum for medical physics experts in radiotherapy.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Feb 18, 2022
PURPOSE: To update the 2011 ESTRO-EFOMP core curriculum (CC) for education and training of medical physics experts (MPE)s working in radiotherapy (RT), in line with recent EU guidelines, and to provide a framework for European countries to develop th...
Adopting Machine Learning Auto-Segmentation Into Radiotherapy Workflow.
Clinical oncology (Royal College of Radiologists (Great Britain))
Feb 17, 2022
Understanding machine learning classifier decisions in automated radiotherapy quality assurance.
Physics in medicine and biology
Jan 17, 2022
The complexity of generating radiotherapy treatments demands a rigorous quality assurance (QA) process to ensure patient safety and to avoid clinically significant errors. Machine learning classifiers have been explored to augment the scope and effic...
A Glimmer of Hope Within the Mountain of Hype - Reviewing the Role of Artificial Intelligence in Radiotherapy.
Clinical oncology (Royal College of Radiologists (Great Britain))
Dec 16, 2021
Deep Learning for Radiotherapy Outcome Prediction Using Dose Data - A Review.
Clinical oncology (Royal College of Radiologists (Great Britain))
Dec 16, 2021
Artificial intelligence, and in particular deep learning using convolutional neural networks, has been used extensively for image classification and segmentation, including on medical images for diagnosis and prognosis prediction. Use in radiotherapy...
Molecular Biology in Treatment Decision Processes-Neuro-Oncology Edition.
International journal of molecular sciences
Dec 10, 2021
Computational approaches including machine learning, deep learning, and artificial intelligence are growing in importance in all medical specialties as large data repositories are increasingly being optimised. Radiation oncology as a discipline is at...
Application of deep learning to auto-delineation of target volumes and organs at risk in radiotherapy.
Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
Oct 26, 2021
The technological advancement heralded the arrival of precision radiotherapy (RT), thereby increasing the therapeutic ratio and decreasing the side effects from treatment. Contour of target volumes (TV) and organs at risk (OARs) in RT is a complicate...
Natural language processing and machine learning to assist radiation oncology incident learning.
Journal of applied clinical medical physics
Oct 5, 2021
PURPOSE: To develop a Natural Language Processing (NLP) and Machine Learning (ML) pipeline that can be integrated into an Incident Learning System (ILS) to assist radiation oncology incident learning by semi-automating incident classification. Our go...
Artificial intelligence in radiation oncology: A review of its current status and potential application for the radiotherapy workforce.
Radiography (London, England : 1995)
Sep 4, 2021
OBJECTIVE: Radiation oncology is a continually evolving speciality. With the development of new imaging modalities and advanced imaging processing techniques, there is an increasing amount of data available to practitioners. In this narrative review,...
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