AIMC Topic: Radiotherapy Dosage
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Liver tumor segmentation based on 3D convolutional neural network with dual scale.
Journal of applied clinical medical physics
Dec 2, 2019
PURPOSE: Liver is one of the organs with a high incidence of tumors in the human body. Malignant liver tumors seriously threaten human life and health. The difficulties of liver tumor segmentation from computed tomography (CT) image are: (a) The cont...
Knowledge-based automated planning with three-dimensional generative adversarial networks.
Medical physics
Nov 29, 2019
PURPOSE: To develop a knowledge-based automated planning pipeline that generates treatment plans without feature engineering, using deep neural network architectures for predicting three-dimensional (3D) dose.
Winter is over: The use of Artificial Intelligence to individualise radiation therapy for breast cancer.
Breast (Edinburgh, Scotland)
Nov 26, 2019
Artificial intelligence demonstrated its value for automated contouring of organs at risk and target volumes as well as for auto-planning of radiation dose distributions in terms of saving time, increasing consistency, and improving dose-volumes para...
A simple knowledge-based tool for stereotactic radiosurgery pre-planning.
Journal of applied clinical medical physics
Nov 19, 2019
We studied the dosimetry of single-isocenter treatment plans generated to treat a solitary intracranial lesion using linac-based stereotactic radiosurgery (SRS). A common metric for evaluating SRS plan quality is the volume of normal brain tissue irr...
Feasibility of two-dimensional dose distribution deconvolution using convolution neural networks.
Medical physics
Nov 6, 2019
PURPOSE: The purpose of this study was to investigate the feasibility of two-dimensional (2D) dose distribution deconvolution using convolutional neural networks (CNNs) instead of an analytical approach for an in-house scintillation detector that has...
Effect of Radiation Doses to the Heart on Survival for Stereotactic Ablative Radiotherapy for Early-stage Non-Small-cell Lung Cancer: An Artificial Neural Network Approach.
Clinical lung cancer
Oct 21, 2019
INTRODUCTION: The cardiac radiation dose is an important predictor of cardiac toxicity and overall survival (OS) for patients with locally advanced non-small-cell lung cancer (NSCLC). However, radiation-induced cardiac toxicity among patients with ea...
Technical Note: Machine learning approaches for range and dose verification in proton therapy using proton-induced positron emitters.
Medical physics
Oct 10, 2019
PURPOSE/OBJECTIVE(S): Online proton range/dose verification based on measurements of proton-induced positron emitters is a promising strategy for quality assurance in proton therapy. Because of the nonlinear correlation between the dose distribution ...
The ideal couch tracking system-Requirements and evaluation of current systems.
Journal of applied clinical medical physics
Sep 19, 2019
INTRODUCTION: Intrafractional motion can cause substantial uncertainty in precision radiotherapy. Traditionally, the target volume is defined to be sufficiently large to cover the tumor in every position. With the robotic treatment couch, a real-time...
Artificial Intelligence in Radiation Oncology.
Hematology/oncology clinics of North America
Sep 11, 2019
The integration of artificial intelligence in the radiation oncologist's workflow has multiple applications and significant potential. From the initial patient encounter, artificial intelligence may aid in pretreatment disease outcome and toxicity pr...
Comparison of Deep Learning-Based and Patch-Based Methods for Pseudo-CT Generation in MRI-Based Prostate Dose Planning.
International journal of radiation oncology, biology, physics
Sep 7, 2019
PURPOSE: Deep learning methods (DLMs) have recently been proposed to generate pseudo-CT (pCT) for magnetic resonance imaging (MRI) based dose planning. This study aims to evaluate and compare DLMs (U-Net and generative adversarial network [GAN]) usin...
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