ReviewPhysics in medicine and biology2014
GPU-based high-performance computing for radiation therapy.
Review in Physics in medicine and biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
33 citing papers in PubMed.
- Review of GPU-based Monte Carlo simulation platforms for transmission and emission tomography in medicine.Physics in medicine and biology · 2025Review
- deepPERFECT: Novel Deep Learning CT Synthesis Method for Expeditious Pancreatic Cancer Radiotherapy.Cancers · 2023Article
- DAART: a deep learning platform for deeply accelerated adaptive radiation therapy for lung cancer.Frontiers in oncology · 2023Article
- A Data-Driven Fragmentation Model for Carbon Therapy GPU-Accelerated Monte-Carlo Dose Recalculation.Frontiers in oncology · 2022Article
- Varian ethos online adaptive radiotherapy for prostate cancer: Early results of contouring accuracy, treatment plan quality, and treatment time.Journal of applied clinical medical physics · 2022Article
- Monte Carlo methods for device simulations in radiation therapy.Physics in medicine and biology · 2021Review
- Recent Developments on gMicroMC: Transport Simulations of Proton and Heavy Ions and Concurrent Transport of Radicals and DNA.International journal of molecular sciences · 2021Article
- Adaptive Radiation Therapy (ART) Strategies and Technical Considerations: A State of the ART Review From NRG Oncology.International journal of radiation oncology, biology, physics · 2021Review
- Improving Proton Dose Calculation Accuracy by Using Deep Learning.Machine learning: science and technology · 2021Article
- Whole-body voxel-based internal dosimetry using deep learning.European journal of nuclear medicine and molecular imaging · 2021Article
- Dose rate determination for preclinical total body irradiation.Physics in medicine and biology · 2020Article
- An introduction to deep learning in medical physics: advantages, potential, and challenges.Physics in medicine and biology · 2020Review
- Metropolis Monte Carlo simulation scheme for fast scattered X-ray photon calculation in CT.Optics express · 2019Article
- Monte Carlo verification of radiotherapy treatments with CloudMC.Radiation oncology (London, England) · 2018Article
- Material elemental decomposition in dual and multi-energy CT via a sparsity-dictionary approach for proton stopping power ratio calculation.Medical physics · 2018Article
- Internal Motion Estimation by Internal-external Motion Modeling for Lung Cancer Radiotherapy.Scientific reports · 2018Article
- Multi-GPU configuration of 4D intensity modulated radiation therapy inverse planning using global optimization.Physics in medicine and biology · 2018Article
- Magnetic resonance image guidance in external beam radiation therapy planning and delivery.Japanese journal of radiology · 2017Review
- Initial development of goCMC: a GPU-oriented fast cross-platform Monte Carlo engine for carbon ion therapy.Physics in medicine and biology · 2017Article
- Accelerated Monte Carlo simulation on the chemical stage in water radiolysis using GPU.Physics in medicine and biology · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Recent developments in radiotherapy therapy demand high computation powers to solve challenging problems in a timely fashion in a clinical environment. The graphics processing unit (GPU), as an emerging high-performance computing platform, has been introduced to radiotherapy. It is particularly attractive due to its high computational power, small size, and low cost for facility deployment and maintenance. Over the past few years, GPU-based high-performance computing in radiotherapy has experienced rapid developments. A tremendous amount of study has been conducted, in which large acceleration factors compared with the conventional CPU platform have been observed. In this paper, we will first give a brief introduction to the GPU hardware structure and programming model. We will then review the current applications of GPU in major imaging-related and therapy-related problems encountered in radiotherapy. A comparison of GPU with other platforms will also be presented.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.