AIMC Topic: Radiation Oncology

Clear Filters Showing 21 to 30 of 119 articles

A joint ESTRO and AAPM guideline for development, clinical validation and reporting of artificial intelligence models in radiation therapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Artificial Intelligence (AI) models in radiation therapy are being developed with increasing pace. Despite this, the radiation therapy community has not widely adopted these models in clinical practice. A cohesive guideline on...

Deformable registration of magnetic resonance images using unsupervised deep learning in neuro-/radiation oncology.

Radiation oncology (London, England)
PURPOSE: Accurate deformable registration of magnetic resonance imaging (MRI) scans containing pathologies is challenging due to changes in tissue appearance. In this paper, we developed a novel automated three-dimensional (3D) convolutional U-Net ba...

[Not Available].

Medical physics
BACKGROUND:: Efficient and accurate delineation of organs at risk (OARs) is a critical procedure for treatment planning and dose evaluation. Deep learning-based auto-segmentation of OARs has shown promising results and is increasingly being used in r...

The role of artificial intelligence in informed patient consent for radiotherapy treatments-a case report.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
Recent advancements in large language models (LMM; e.g., ChatGPT (OpenAI, San Francisco, California, USA)) have seen widespread use in various fields, including healthcare. This case study reports on the first use of LMM in a pretreatment discussion ...

ChatGPT and research in radiation oncology: Correspondence.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology

NRG Oncology Assessment of Artificial Intelligence Deep Learning-Based Auto-segmentation for Radiation Therapy: Current Developments, Clinical Considerations, and Future Directions.

International journal of radiation oncology, biology, physics
Deep learning neural networks (DLNN) in Artificial intelligence (AI) have been extensively explored for automatic segmentation in radiotherapy (RT). In contrast to traditional model-based methods, data-driven AI-based models for auto-segmentation hav...

Framework for Radiation Oncology Department-wide Evaluation and Implementation of Commercial Artificial Intelligence Autocontouring.

Practical radiation oncology
PURPOSE: Artificial intelligence (AI)-based autocontouring in radiation oncology has potential benefits such as standardization and time savings. However, commercial AI solutions require careful evaluation before clinical integration. We developed a ...

Current Strengths and Weaknesses of ChatGPT as a Resource for Radiation Oncology Patients and Providers.

International journal of radiation oncology, biology, physics
PURPOSE: Chat Generative Pre-Trained Transformer (ChatGPT), an artificial intelligence program that uses natural language processing to generate conversational-style responses to questions or inputs, is increasingly being used by both patients and he...

Automation and artificial intelligence in radiation therapy treatment planning.

Journal of medical radiation sciences
Automation and artificial intelligence (AI) is already possible for many radiation therapy planning and treatment processes with the aim of improving workflows and increasing efficiency in radiation oncology departments. Currently, AI technology is a...