AIMC Topic: Radiotherapy Dosage
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Deep learning-based synthetic CT generation for MR-only radiotherapy of prostate cancer patients with 0.35T MRI linear accelerator.
Journal of applied clinical medical physics
Jun 28, 2021
PURPOSE: To develop a deep learning model to generate synthetic CT for MR-only radiotherapy of prostate cancer patients treated with 0.35 T MRI linear accelerator.
Interobserver variability in organ at risk delineation in head and neck cancer.
Radiation oncology (London, England)
Jun 28, 2021
BACKGROUND: In radiotherapy inaccuracy in organ at risk (OAR) delineation can impact treatment plan optimisation and treatment plan evaluation. Brouwer et al. showed significant interobserver variability (IOV) in OAR delineation in head and neck canc...
Automation in radiotherapy treatment planning: Examples of use in clinical practice and future trends for a complete automated workflow.
Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
Jun 24, 2021
Modern radiotherapy treatment planning is a complex and time-consuming process that requires the skills of experienced users to obtain quality plans. Since the early 2000s, the automation of this planning process has become an important research topi...
The dosimetric impact of deep learning-based auto-segmentation of organs at risk on nasopharyngeal and rectal cancer.
Radiation oncology (London, England)
Jun 23, 2021
PURPOSE: To investigate the dosimetric impact of deep learning-based auto-segmentation of organs at risk (OARs) on nasopharyngeal and rectal cancer.
A hierarchical deep reinforcement learning framework for intelligent automatic treatment planning of prostate cancer intensity modulated radiation therapy.
Physics in medicine and biology
Jun 23, 2021
We have previously proposed an intelligent automatic treatment planning (IATP) framework that builds a virtual treatment planner network (VTPN) to operate a treatment planning system (TPS) to generate high-quality radiation therapy (RT) treatment pla...
Technical Note: Dose prediction for head and neck radiotherapy using a three-dimensional dense dilated U-net architecture.
Medical physics
Jun 22, 2021
PURPOSE: Radiation therapy treatment planning is a time-consuming and iterative manual process. Consequently, plan quality varies greatly between and within institutions. Artificial intelligence shows great promise in improving plan quality and reduc...
Technical Note: Dose prediction for radiation therapy using feature-based losses and One Cycle Learning.
Medical physics
Jun 22, 2021
PURPOSE: To present the technical details of the runner-up model in the open knowledge-based planning (OpenKBP) challenge for the dose-volume histogram (DVH) stream. The model was designed to ensure simple and reproducible training, without the neces...
Independent verification of brachytherapy treatment plan by using deep learning inference modeling.
Physics in medicine and biology
Jun 16, 2021
This study aims to develop a deep learning-based strategy for treatment plan check and verification of high-dose rate (HDR) brachytherapy. A deep neural network was trained to verify the dwell positions and times for a given input brachytherapy isodo...
Implementation of deep learning-based auto-segmentation for radiotherapy planning structures: a workflow study at two cancer centers.
Radiation oncology (London, England)
Jun 8, 2021
PURPOSE: We recently described the validation of deep learning-based auto-segmented contour (DC) models for organs at risk (OAR) and clinical target volumes (CTV). In this study, we evaluate the performance of implemented DC models in the clinical ra...
Radiotherapy Dosage
Humans
Head and Neck Neoplasms
Male
Radiotherapy, Intensity-Modulated
Algorithms
Prostatic Neoplasms
Organs at Risk
Central Nervous System Neoplasms
Deep Learning
Workflow
Radiotherapy Planning, Computer-Assisted
Prognosis
Image Processing, Computer-Assisted
Tomography, X-Ray Computed
Health Plan Implementation
DVHnet: A deep learning-based prediction of patient-specific dose volume histograms for radiotherapy planning.
Medical physics
Apr 18, 2021
PURPOSE: To develop a deep learning method to predict patient-specific dose volume histograms (DVHs) for radiotherapy planning.
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