AIMC Topic: Organs at Risk

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Deep Learning-Based Dose Prediction for Automated, Individualized Quality Assurance of Head and Neck Radiation Therapy Plans.

Practical radiation oncology Jan 24, 2023
PURPOSE: This study aimed to use deep learning-based dose prediction to assess head and neck (HN) plan quality and identify suboptimal plans.
Humans Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Deep Learning Organs at Risk
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A clinical and time savings evaluation of a deep learning automatic contouring algorithm.

Medical dosimetry : official journal of the American Association of Medical Dosimetrists Dec 20, 2022
Automatic contouring algorithms may streamline clinical workflows by reducing normal organ-at-risk (OAR) contouring time. Here we report the first comprehensive quantitative and qualitative evaluation, along with time savings assessment for a prototy...
Humans Algorithms Retrospective Studies Deep Learning Organs at Risk Neck Radiotherapy Planning, Computer-Assisted
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Deep learning architecture with transformer and semantic field alignment for voxel-level dose prediction on brain tumors.

Medical physics Dec 5, 2022
PURPOSE: The use of convolution neural networks (CNN) to accurately predict dose distributions can accelerate intensity-modulated radiation therapy (IMRT) planning. The purpose of our study is to develop a novel deep learning architecture for precise...
Radiotherapy Dosage Radiotherapy, Intensity-Modulated Radiotherapy Planning, Computer-Assisted Humans Semantics Retrospective Studies Brain Neoplasms Deep Learning Organs at Risk
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Improved accuracy of auto-segmentation of organs at risk in radiotherapy planning for nasopharyngeal carcinoma based on fully convolutional neural network deep learning.

Oral oncology Nov 26, 2022
OBJECTIVE: We examined a modified encoder-decoder architecture-based fully convolutional neural network, OrganNet, for simultaneous auto-segmentation of 24 organs at risk (OARs) in the head and neck, followed by validation tests and evaluation of cli...
Neural Networks, Computer Deep Learning Humans Radiotherapy Planning, Computer-Assisted Image Processing, Computer-Assisted Nasopharyngeal Carcinoma Organs at Risk Nasopharyngeal Neoplasms
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Patient-specific transfer learning for auto-segmentation in adaptive 0.35 T MRgRT of prostate cancer: a bi-centric evaluation.

Medical physics Nov 7, 2022
BACKGROUND: Online adaptive radiation therapy (RT) using hybrid magnetic resonance linear accelerators (MR-Linacs) can administer a tailored radiation dose at each treatment fraction. Daily MR imaging followed by organ and target segmentation adjustm...
Male Image Processing, Computer-Assisted Prostatic Neoplasms Machine Learning Tomography, X-Ray Computed Organs at Risk Radiotherapy Planning, Computer-Assisted Humans Artificial Intelligence
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Deep learning empowered volume delineation of whole-body organs-at-risk for accelerated radiotherapy.

Nature communications Nov 2, 2022
In radiotherapy for cancer patients, an indispensable process is to delineate organs-at-risk (OARs) and tumors. However, it is the most time-consuming step as manual delineation is always required from radiation oncologists. Herein, we propose a ligh...
Deep Learning Image Processing, Computer-Assisted Organs at Risk Tomography, X-Ray Computed Neoplasms Humans
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Comparison of atlas-based and deep learning methods for organs at risk delineation on head-and-neck CT images using an automated treatment planning system.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Nov 1, 2022
BACKGROUND AND PURPOSE: To investigate the performance of head-and-neck (HN) organs-at-risk (OAR) automatic segmentation (AS) using four atlas-based (ABAS) and two deep learning (DL) solutions.
Radiotherapy Planning, Computer-Assisted Humans Tomography, X-Ray Computed Head and Neck Neoplasms Deep Learning Organs at Risk
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Efficient dose-volume histogram-based pretreatment patient-specific quality assurance methodology with combined deep learning and machine learning models for volumetric modulated arc radiotherapy.

Medical physics Oct 17, 2022
BACKGROUND: Weak correlation between gamma passing rates and dose differences in target volumes and organs at risk (OARs) has been reported in several studies. Evaluation on the differences between planned dose-volume histogram (DVH) and reconstructe...
Radiotherapy Dosage Radiotherapy, Intensity-Modulated Organs at Risk Humans Deep Learning Radiotherapy Planning, Computer-Assisted Machine Learning Head and Neck Neoplasms
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Clinical evaluation of deep learning and atlas-based auto-segmentation for critical organs at risk in radiation therapy.

Journal of medical radiation sciences Sep 23, 2022
INTRODUCTION: Contouring organs at risk (OARs) is a time-intensive task that is a critical part of radiation therapy. Atlas-based automatic segmentation has shown some success at reducing this time burden on practitioners; however, this method often ...
Head and Neck Neoplasms Deep Learning Radiotherapy Planning, Computer-Assisted Organs at Risk Humans Image Processing, Computer-Assisted Tomography, X-Ray Computed
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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 Sep 23, 2022
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...
Image Processing, Computer-Assisted Humans Radiation Oncology Bone and Bones Tomography, X-Ray Computed Deep Learning Organs at Risk Child Radiotherapy Planning, Computer-Assisted
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