AIMC Topic: Radiotherapy, Computer-Assisted
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Accurate 3D-dose-based generation of MLC segments for robotic radiotherapy.
Physics in medicine and biology
Aug 31, 2020
Radiotherapy treatment planning requires accurate modeling of the delivered patient dose, including radiation scatter effects, multi-leaf collimator (MLC) leaf transmission, interleaf-leakage, etc. In fluence map optimization (FMO), a simple dose mod...
Feasibility of Multiparametric Positron Emission Tomography/Magnetic Resonance Imaging as a One-Stop Shop for Radiation Therapy Planning for Patients with Head and Neck Cancer.
International journal of radiation oncology, biology, physics
Jul 16, 2020
PURPOSE: Multiparametric positron emission tomography (PET)/magnetic resonance imaging (MRI) as a one-stop shop for radiation therapy (RT) planning has great potential but is technically challenging. We studied the feasibility of performing multipara...
Magnetic Resonance Imaging
Multimodal Imaging
Feasibility Studies
Tomography, X-Ray Computed
Radiotherapy Dosage
Radiopharmaceuticals
Deep Learning
Humans
Patient Positioning
Positron-Emission Tomography
Head and Neck Neoplasms
Radiotherapy, Computer-Assisted
Neural Networks, Computer
Fluorodeoxyglucose F18
Prospective Studies
The emerging roles of artificial intelligence in cancer drug development and precision therapy.
Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie
May 20, 2020
Artificial intelligence (AI) has strong logical reasoning ability and independent learning ability, which can simulate the thinking process of the human brain. AI technologies such as machine learning can profoundly optimize the existing mode of anti...
Comparison of statistical machine learning models for rectal protocol compliance in prostate external beam radiation therapy.
Medical physics
Feb 19, 2020
PURPOSE: Limiting the dose to the rectum can be one of the most challenging aspects of creating a dosimetric external beam radiation therapy (EBRT) plan for prostate cancer treatment. Rectal sparing devices such as hydrogel spacers offer the prospect...
Many-isocenter optimization for robotic radiotherapy.
Physics in medicine and biology
Feb 10, 2020
Despite significant dosimetric gains, clinical implementation of the 4π non-coplanar radiotherapy on the widely available C-arm gantry system is hindered by limited clearance, and the need to perform complex coordinated gantry and couch motion. A rob...
Development of a robot-assisted ultrasound-guided radiation therapy (USgRT).
International journal of computer assisted radiology and surgery
Dec 12, 2019
PURPOSE: Radiation treatment is improved by the use of image-guided workflows. This work pursues the approach of using ultrasound (US) as a real-time imaging modality. The primary focus of this study is to develop and test a breathing and motion cont...
Meeting of the Minds: Considering the Real Impact of Artificial Intelligence.
Journal of medical imaging and radiation sciences
Nov 26, 2019
A Super-Learner Model for Tumor Motion Prediction and Management in Radiation Therapy: Development and Feasibility Evaluation.
Scientific reports
Oct 16, 2019
In cancer radiation therapy, large tumor motion due to respiration can lead to uncertainties in tumor target delineation and treatment delivery, thus making active motion management an essential step in thoracic and abdominal tumor treatment. In curr...
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...
Deep-learning-assisted automatic digitization of applicators in 3D CT image-based high-dose-rate brachytherapy of gynecological cancer.
Brachytherapy
Jul 22, 2019
PURPOSE: Applicator digitization is one of the most critical steps in 3D high-dose-rate brachytherapy (HDRBT) treatment planning. Motivated by recent advances in deep-learning, we propose a deep-learning-assisted applicator digitization method for 3D...
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