AI Medical Compendium Journal:
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology

Showing 71 to 80 of 120 articles

Clinical evaluation of a deep learning model for segmentation of target volumes in breast cancer radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE/OBJECTIVE(S): Precise segmentation of clinical target volumes (CTV) in breast cancer is indispensable for state-of-the art radiotherapy. Despite international guidelines, significant intra- and interobserver variability exists, negatively imp...

Dose prediction via distance-guided deep learning: Initial development for nasopharyngeal carcinoma radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Geometric information such as distance information is essential for dose calculations in radiotherapy. However, state-of-the-art dose prediction methods use only binary masks without distance information. This study aims to de...

Deep learning improves image quality and radiomics reproducibility for high-speed four-dimensional computed tomography reconstruction.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Hybrid iterative reconstruction (HIR) is the most commonly used algorithm for four-dimensional computed tomography (4DCT) reconstruction due to its high speed. However, the image quality is worse than that of model-based itera...

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...

Deep learning driven predictive treatment planning for adaptive radiotherapy of lung cancer.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: To develop a novel deep learning algorithm of sequential analysis, Seq2Seq, for predicting weekly anatomical changes of lung tumor and esophagus during definitive radiotherapy, incorporate the potential tumor shrinkage into a ...

Deep learning radiomics model related with genomics phenotypes for lymph node metastasis prediction in colorectal cancer.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: The preoperative lymph node (LN) status is important for the treatment of colorectal cancer (CRC). Here, we established and validated a deep learning (DPL) model for predicting lymph node metastasis (LNM) in CRC.

Deep learning-based GTV contouring modeling inter- and intra- observer variability in sarcomas.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: The delineation of the gross tumor volume (GTV) is a critical step for radiation therapy treatment planning. The delineation procedure is typically performed manually which exposes two major issues: cost and reproducibility. D...

Deep learning model for automatic contouring of cardiovascular substructures on radiotherapy planning CT images: Dosimetric validation and reader study based clinical acceptability testing.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Large radiotherapy (RT) planning imaging datasets with consistently contoured cardiovascular structures are essential for robust cardiac radiotoxicity research in thoracic cancers. This study aims to develop and validate a hig...

Image-based deep learning model for predicting pathological response in rectal cancer using post-chemoradiotherapy magnetic resonance imaging.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
INTRODUCTION: To develop an image-based deep learning model for predicting pathological response in rectal cancer using post-chemoradiotherapy magnetic resonance (MR) imaging.

Metrics to evaluate the performance of auto-segmentation for radiation treatment planning: A critical review.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Advances in artificial intelligence-based methods have led to the development and publication of numerous systems for auto-segmentation in radiotherapy. These systems have the potential to decrease contour variability, which has been associated with ...