AIMC Topic: Radiation Oncology

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Auto-segmentation of important centers of growth in the pediatric skeleton to consider during radiation therapy based on deep learning.

Medical physics
BACKGROUND: Routinely delineating of important skeletal growth centers is imperative to mitigate radiation-induced growth abnormalities for pediatric cancer patients treated with radiotherapy. However, it is hindered by several practical problems, in...

Artificial intelligence in radiotherapy.

Seminars in cancer biology
Radiotherapy is a discipline closely integrated with computer science. Artificial intelligence (AI) has developed rapidly over the past few years. With the explosive growth of medical big data, AI promises to revolutionize the field of radiotherapy t...

Clinical Validation of a Deep-Learning Segmentation Software in Head and Neck: An Early Analysis in a Developing Radiation Oncology Center.

International journal of environmental research and public health
BACKGROUND: Organs at risk (OARs) delineation is a crucial step of radiotherapy (RT) treatment planning workflow. Time-consuming and inter-observer variability are main issues in manual OAR delineation, mainly in the head and neck (H & N) district. D...

Digital skills of therapeutic radiographers/radiation therapists - Document analysis for a European educational curriculum.

Radiography (London, England : 1995)
INTRODUCTION: It is estimated that around 50% of cancer patients require Radiotherapy (RT) at some point during their treatment, hence Therapeutic Radiographers/Radiation Therapists (TR/RTTs) have a key role to play in patient management. It is essen...

Training, validation, and clinical implementation of a deep-learning segmentation model for radiotherapy of loco-regional breast cancer.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
AIM: To train and validate a comprehensive deep-learning (DL) segmentation model for loco-regional breast cancer with the aim of clinical implementation.

Artificial intelligence based deconvolving on megavoltage photon beam profiles for radiotherapy applications.

Physics in medicine and biology
. 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
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...