AIMC Topic: Radiotherapy Planning, Computer-Assisted

Clear Filters Showing 581 to 590 of 778 articles

Winter is over: The use of Artificial Intelligence to individualise radiation therapy for breast cancer.

Breast (Edinburgh, Scotland)
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
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
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...

Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning.

Nature biomedical engineering
Tomographic imaging using penetrating waves generates cross-sectional views of the internal anatomy of a living subject. For artefact-free volumetric imaging, projection views from a large number of angular positions are required. Here we show that a...

Improving automatic delineation for head and neck organs at risk by Deep Learning Contouring.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
INTRODUCTION: Adequate head and neck (HN) organ-at-risk (OAR) delineation is crucial for HN radiotherapy and for investigating the relationships between radiation dose to OARs and radiation-induced side effects. The automatic contouring algorithms th...

Evaluation of a deep learning-based pelvic synthetic CT generation technique for MRI-based prostate proton treatment planning.

Physics in medicine and biology
The purpose of this work is to validate the application of a deep learning-based method for pelvic synthetic CT (sCT) generation that can be used for prostate proton beam therapy treatment planning. We propose to integrate dense block minimization in...

Optimizing robot motion for robotic ultrasound-guided radiation therapy.

Physics in medicine and biology
An important aspect of robotic radiation therapy is active compensation of target motion. Recently, ultrasound has been proposed to obtain real-time volumetric images of abdominal organ motion. One approach to realize flexible probe placement through...

The ideal couch tracking system-Requirements and evaluation of current systems.

Journal of applied clinical medical physics
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
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...

2D ultrasound imaging based intra-fraction respiratory motion tracking for abdominal radiation therapy using machine learning.

Physics in medicine and biology
We have previously developed a robotic ultrasound imaging system for motion monitoring in abdominal radiation therapy. Owing to the slow speed of ultrasound image processing, our previous system could only track abdominal motions under breath-hold. T...