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

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...
Parallel Processing01:20

Parallel Processing

The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

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...

You might also read

Related Articles

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

Sort by
Same author

Erratum: Hypoxia-induced m6A demethylase ALKBH5 promotes ovarian cancer tumorigenicity by decreasing methylation of the lncRNA RMRP.

American journal of cancer research·2026
Same author

Impact of serum ferritin on the efficacy of hydrocortisone in septic patients: a retrospective cohort study.

BMC infectious diseases·2026
Same author

Association between blood urea nitrogen trajectory phenotypes and prognosis in patients with sepsis: a multicenter retrospective cohort study.

BMC infectious diseases·2026
Same author

Effect of early antiplatelet therapy on 30-day mortality after coronary artery bypass grafting: a retrospective target trial emulation using the MIMIC-IV database.

BMJ open·2026
Same author

Exposure to low-dose ionizing radiation and dementia mortality in Canadian nuclear power plant workers.

Environmental research·2026
Same author

Extracting Histologic Features to Distinguish Primary and Metastatic Squamous Cell Carcinoma of the Lung.

Pathology international·2026
Same journal

Generalizable framework for multi-site bone density prediction using non-dominant wrist optical biomarkers.

Biomedical optics express·2026
Same journal

Erratum: Review of dynamic optical coherence tomography for intracellular motility [Invited]: errata.

Biomedical optics express·2026
Same journal

Digital-micromirror-device-based illumination strategies for background suppression in single-molecule localization microscopy.

Biomedical optics express·2026
Same journal

Synergistic combination of convective self-assembly and hollow core fiber for sensitive SERS detection of glucose molecules.

Biomedical optics express·2026
Same journal

Multimodal diagnostic network integrating infrared and mass spectra for lung cancer.

Biomedical optics express·2026
Same journal

Multimodal Optical Biosensing for Precision Medicine and Healthcare: Introduction to the feature issue.

Biomedical optics express·2026
See all related articles

Related Experiment Video

Updated: May 31, 2026

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
11:34

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

Published on: December 3, 2013

Off-axis quantitative phase imaging processing using CUDA: toward real-time applications.

Hoa Pham, Huafeng Ding, Nahil Sobh

    Biomedical Optics Express
    |July 14, 2011
    PubMed
    Summary
    This summary is machine-generated.

    We developed a fast phase reconstruction algorithm for real-time off-axis Quantitative Phase Imaging (QPI). This GPU-accelerated method achieves video rates for large images, enabling high-speed imaging.

    Keywords:
    (100.5070) Phase retrieval(100.5088) Phase unwrapping(170.6920) Time-resolved imaging(180.3170) Interference microscopy

    More Related Videos

    A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells
    10:37

    A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells

    Published on: August 22, 2025

    An Experimental Protocol for Assessing the Performance of New Ultrasound Probes Based on CMUT Technology in Application to Brain Imaging
    16:01

    An Experimental Protocol for Assessing the Performance of New Ultrasound Probes Based on CMUT Technology in Application to Brain Imaging

    Published on: September 24, 2017

    Related Experiment Videos

    Last Updated: May 31, 2026

    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
    11:34

    High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

    Published on: December 3, 2013

    A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells
    10:37

    A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells

    Published on: August 22, 2025

    An Experimental Protocol for Assessing the Performance of New Ultrasound Probes Based on CMUT Technology in Application to Brain Imaging
    16:01

    An Experimental Protocol for Assessing the Performance of New Ultrasound Probes Based on CMUT Technology in Application to Brain Imaging

    Published on: September 24, 2017

    Area of Science:

    • Optics and Photonics
    • Computational Imaging
    • Biomedical Engineering

    Background:

    • Quantitative Phase Imaging (QPI) enables label-free cell imaging.
    • Real-time processing of QPI data is computationally intensive.
    • Current methods often struggle with high-resolution, high-speed acquisition.

    Purpose of the Study:

    • To develop a GPU-accelerated algorithm for real-time off-axis QPI.
    • To significantly enhance the processing speed of phase reconstruction and unwrapping.
    • To enable video-rate acquisition and visualization of megapixel QPI data.

    Main Methods:

    • Implemented a phase reconstruction algorithm using NVIDIA's CUDA programming model.
    • Utilized Goldstein's algorithm for the phase unwrapping component.
    • Mapped phase extraction and unwrapping processes to the GPU for parallel processing.

    Main Results:

    • Achieved a speed-up of over 18.8× compared to CPU processing.
    • Enabled real-time video-rate acquisition for megapixel images.
    • Demonstrated simultaneous processing of multiple images for high throughput.

    Conclusions:

    • GPU acceleration significantly enhances QPI processing speed.
    • The developed CUDA implementation facilitates high-speed, high-throughput, real-time QPI.
    • This advancement supports rapid imaging and visualization in various scientific applications.