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 Concept Videos

Computed Tomography01:10

Computed Tomography

6.4K
Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
6.4K
Imaging Studies I: CT and MRI01:14

Imaging Studies I: CT and MRI

467
Introduction: MRI and CT scans are crucial advancements in medical imaging techniques, playing a vital role in diagnosing conditions related to the gastrointestinal (GI) system. Each scan serves distinct purposes, targets specific areas, and requires unique nursing duties.
Description of the Procedures
Computed Tomography (CT) scan:
Computed Tomography (CT) scans use X-ray technology to generate detailed images of bones, organs, and tissues. During the scan, the patient lies on a moving table...
467
Imaging Studies for Cardiovascular System V: CT01:28

Imaging Studies for Cardiovascular System V: CT

74
Cardiac computed tomography (CT) scanning is an advanced cardiac imaging technique that utilizes CT technology, with or without intravenous (IV) contrast, to produce accurate cross-sectional virtual slices of specific areas of the heart, coronary circulation, and major blood vessels such as the aorta, pulmonary veins, and arteries. The computer processes these slices to generate three-dimensional images. Multidetector CT (MDCT) is a rapid form of CT scanning that captures multiple slices...
74
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

59
DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
59

You might also read

Related Articles

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

Sort by
Same author

Investigating the capabilities of large vision language models in dog emotion recognition.

Scientific reports·2025
Same author

Does the tail show when the nose knows? Artificial intelligence outperforms human experts at predicting detection dogs finding their target through tail kinematics.

Royal Society open science·2025
Same author

Dog facial landmarks detection and its applications for facial analysis.

Scientific reports·2025
Same author

Correction: Automated recognition of emotional states of horses from facial expressions.

PloS one·2025
Same author

Comparison between AI and human expert performance in acute pain assessment in sheep.

Scientific reports·2025
Same author

Automated landmark-based cat facial analysis and its applications.

Frontiers in veterinary science·2024

Related Experiment Video

Updated: Sep 20, 2025

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

3.0K

ActiveNaf: A novel NeRF-based approach for low-dose CT image reconstruction through active learning.

Ahmad Zidane1, Ilan Shimshoni1

  • 1Department of Information Systems, University of Haifa, Haifa, Israel.

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)
|May 23, 2025
PubMed
Summary

This study introduces a novel method combining Neural Attenuation Fields (NAF) and active learning to reduce radiation dose in CT imaging. The approach achieves high-quality 3D reconstructions using fewer X-ray projections, enhancing patient safety.

Keywords:
Active learningCT reconstructionLow-dose CTNeural radiance fields NeRFSparse-view CT

More Related Videos

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
14:08

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

42.8K
Time-Resolved, Dynamic Computed Tomography Angiography for Characterization of Aortic Endoleaks and Treatment Guidance via 2D-3D Fusion-Imaging
09:32

Time-Resolved, Dynamic Computed Tomography Angiography for Characterization of Aortic Endoleaks and Treatment Guidance via 2D-3D Fusion-Imaging

Published on: December 9, 2021

3.1K

Related Experiment Videos

Last Updated: Sep 20, 2025

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography
04:48

Application of Deep Learning-Based Medical Image Segmentation via Orbital Computed Tomography

Published on: November 30, 2022

3.0K
Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images
14:08

Automated Midline Shift and Intracranial Pressure Estimation based on Brain CT Images

Published on: April 13, 2013

42.8K
Time-Resolved, Dynamic Computed Tomography Angiography for Characterization of Aortic Endoleaks and Treatment Guidance via 2D-3D Fusion-Imaging
09:32

Time-Resolved, Dynamic Computed Tomography Angiography for Characterization of Aortic Endoleaks and Treatment Guidance via 2D-3D Fusion-Imaging

Published on: December 9, 2021

3.1K

Area of Science:

  • Medical Imaging
  • Computational Imaging
  • Artificial Intelligence in Healthcare

Background:

  • Conventional CT imaging poses radiation risks for patients needing repeat scans.
  • There is a critical need for effective dose-reduction techniques in CT imaging.
  • Maintaining image quality during dose reduction is a significant challenge.

Purpose of the Study:

  • To develop a method for reducing radiation doses in CT imaging without compromising image quality.
  • To optimize CT reconstructions using a limited number of X-ray projections.
  • To combine Neural Attenuation Fields (NAF) with active learning for improved CT reconstruction.

Main Methods:

  • A secondary neural network predicts the Peak Signal-to-Noise Ratio (PSNR) of 2D projections generated by NAF.
  • An active learning strategy utilizes PSNR predictions to select the most informative X-ray projections.
  • An iterative projection acquisition process is employed, contrasting with conventional single-session acquisition.

Main Results:

  • The proposed method achieves high-quality 3D CT reconstructions from sparse data.
  • Significant improvements in image quality metrics (PSNR3D, SSIM3D, PSNR2D) were observed compared to the baseline.
  • The method attained equivalent image quality using 36 projections compared to the baseline's 60 projections.

Conclusions:

  • The approach enables high-quality 3D CT reconstructions with significantly reduced radiation exposure.
  • Clearer and more detailed anatomical images are produced from sparse projection data.
  • This work advances safer and more efficient medical imaging procedures.