Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Feb 25, 2026

Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

10.1K

Deep architecture neural network-based real-time image processing for image-guided radiotherapy.

Shinichiro Mori1

  • 1Research Center for Charged Particle Therapy, National Institute of Radiological Sciences, Inage-ku, Chiba 263-8555, Japan..

Physica Medica : PM : an International Journal Devoted to the Applications of Physics to Medicine and Biology : Official Journal of the Italian Association of Biomedical Physics (AIFB)
|July 27, 2017
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Prognostic impact of KMT2A-PTD in acute myeloid leukemia in the NGS era: a multicenter retrospective study.

Annals of hematology·2026
Same author

[Utility of acute-phase cerebral blood flow single photon emission computed tomography (SPECT) for evaluating the pathophysiology of Bickerstaff brainstem encephalitis with decorticate posturing].

Rinsho shinkeigaku = Clinical neurology·2026
Same author

Invasive Aspergillus Sinusitis Masquerading as Hypertrophic Pachymeningitis Complicated by a Ruptured Infectious Internal Carotid Artery Aneurysm.

Internal medicine (Tokyo, Japan)·2026
Same author

Natalizumab Escalation Early in the Disease Course of Pediatric-Onset Multiple Sclerosis: Two Japanese Cases.

Pediatric neurology·2026
Same author

Prospective Clinical Outcomes of Cardiac Stereotactic Body Radiotherapy for Refractory Ventricular Tachycardia　- Insights From Dose Distribution in Survivors.

Circulation journal : official journal of the Japanese Circulation Society·2026
Same author

Combined inhibition of complement C5 and neonatal Fc receptor in refractory generalized myasthenia gravis: A report of two cases.

Journal of neuroimmunology·2026
Same journal

Proton RBE for in vivo model systems: LET and dose dependencies for early and late biological endpoints.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)·2026
Same journal

AI-augmented thyroid scintigraphy for robust classification of disease.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)·2026
Same journal

Updating national diagnostic reference levels for adult cardiac interventional procedures in Switzerland.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)·2026
Same journal

Adoption of AI-driven automation and adaptive radiotherapy in clinical practice: results from a national survey.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)·2026
Same journal

Sivan Unit (SU) for standardization of voxel intensity in CBCT: A multi-vendor, multi-centric validation study.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)·2026
Same journal

VIT-MBRT, a GPU accelerated Monte Carlo tool for investigations on preclinical minibeam radiation therapy.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)·2026
See all related articles

Researchers developed novel neural networks for real-time X-ray fluoroscopic image denoising, achieving 30 frames per second processing on standard computers for improved image-guided radiotherapy.

Area of Science:

  • Medical Imaging
  • Radiotherapy
  • Artificial Intelligence

Background:

  • Real-time image processing is crucial for image-guided radiotherapy.
  • Evaluating neural network models for various imaging modalities, including X-ray fluoroscopy, is essential.

Purpose of the Study:

  • To develop real-time image processing techniques for image-guided radiotherapy.
  • To evaluate neural network models for X-ray fluoroscopic image denoising and contrast enhancement.

Main Methods:

  • Two residual network architectures, a convolutional autoencoder (rCAE) and a convolutional neural network (rCNN), were designed.
  • Network parameters, including convolutional kernel size and layer count, were optimized.
  • Models were trained using noisy input images to achieve output quality close to ground-truth images processed with CLAHE.
Keywords:
Computer-assistedFluoroscopyImage processingNeural network modelRadiation therapy

More Related Videos

PET and MRI Guided Irradiation of a Glioblastoma Rat Model Using a Micro-irradiator
10:48

PET and MRI Guided Irradiation of a Glioblastoma Rat Model Using a Micro-irradiator

Published on: December 28, 2017

10.1K

Related Experiment Videos

Last Updated: Feb 25, 2026

Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

10.1K
PET and MRI Guided Irradiation of a Glioblastoma Rat Model Using a Micro-irradiator
10:48

PET and MRI Guided Irradiation of a Glioblastoma Rat Model Using a Micro-irradiator

Published on: December 28, 2017

10.1K

Main Results:

  • Networks with more than 6 convolutional layers and kernels >5x5 improved image quality but not in real-time.
  • Optimized rCAEs (>3 convolutions) and rCNNs (>12 convolutions) with pooling/upsampling layers achieved real-time processing at 30 fps.
  • Acceptable image quality was maintained during real-time processing.

Conclusions:

  • The developed neural network models enable real-time image processing for contrast enhancement and denoising.
  • This advancement can be achieved using conventional modern personal computers.
  • The findings support the integration of these networks into image-guided radiotherapy systems.