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

Three-Dimensional Microscopy in Microbiology01:28

Three-Dimensional Microscopy in Microbiology

Three-dimensional imaging techniques are essential in cell biology, allowing researchers to visualize intricate cellular structures with high resolution. Two prominent methods, Differential Interference Contrast Microscopy (DIC) and Confocal Scanning Laser Microscopy (CSLM), provide distinct advantages for imaging live and thick specimens, respectively.Differential Interference Contrast MicroscopyDIC microscopy enhances contrast in transparent, unstained samples by converting phase...
Phase Contrast and Differential Interference Contrast Microscopy01:26

Phase Contrast and Differential Interference Contrast Microscopy

Phase-Contrast Microscopes
In-phase-contrast microscopes, interference between light directly passing through a cell and light refracted by cellular components is used to create high-contrast, high-resolution images without staining. It is the oldest and simplest type of microscope that creates an image by altering the wavelengths of light rays passing through the specimen. Altered wavelength paths are created using an annular stop in the condenser. The annular stop produces a hollow cone of...

You might also read

Related Articles

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

Sort by
Same author

Large-Scale Evaluation of Machine Learning Models in Identifying Follow-Up Recommendations in Radiology Reports.

Radiology·2025
Same author

Towards fair decentralized benchmarking of healthcare AI algorithms with the Federated Tumor Segmentation (FeTS) challenge.

Nature communications·2025
Same author

Machine learning reveals distinct neuroanatomical signatures of cardiovascular and metabolic diseases in cognitively unimpaired individuals.

Nature communications·2025
Same author

Machine learning-based prognostic subgrouping of glioblastoma: A multicenter study.

Neuro-oncology·2024
Same author

Relationship between MRI brain-age heterogeneity, cognition, genetics and Alzheimer's disease neuropathology.

EBioMedicine·2024
Same author

Genetic and clinical correlates of two neuroanatomical AI dimensions in the Alzheimer's disease continuum.

Translational psychiatry·2024
Same journal

Bayesian Convolutional Neural Networks in Medical Imaging Classification: A Promising Solution for Deep Learning Limits in Data Scarcity Scenarios.

Journal of digital imaging·2023
Same journal

Detecting and Characterizing Inferior Vena Cava Filters on Abdominal Computed Tomography with Data-Driven Computational Frameworks.

Journal of digital imaging·2023
Same journal

DMCA-GAN: Dual Multilevel Constrained Attention GAN for MRI-Based Hippocampus Segmentation.

Journal of digital imaging·2023
Same journal

Left Ventricular Myocardial Dysfunction Evaluation in Thalassemia Patients Using Echocardiographic Radiomic Features and Machine Learning Algorithms.

Journal of digital imaging·2023
Same journal

Public Imaging Datasets of Gastrointestinal Endoscopy for Artificial Intelligence: a Review.

Journal of digital imaging·2023
Same journal

External Validation of Robust Radiomic Signature to Predict 2-Year Overall Survival in Non-Small-Cell Lung Cancer.

Journal of digital imaging·2023
See all related articles

Related Experiment Video

Updated: May 24, 2026

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification (ADCI) and Dose Estimation
10:33

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification (ADCI) and Dose Estimation

Published on: September 4, 2017

DicomBrowser: software for viewing and modifying DICOM metadata.

Kevin A Archie1, Daniel S Marcus

  • 1Mallinckrodt Institute of Radiology, Washington University School of Medicine, Campus Box 8225, Saint Louis, MO 63110, USA. karchie@wustl.edu

Journal of Digital Imaging
|February 22, 2012
PubMed
Summary
This summary is machine-generated.

DicomBrowser software facilitates research imaging by enabling flexible modification of Digital Imaging and Communications in Medicine (DICOM) data. This tool bridges clinical DICOM standards with specialized research needs for easier data handling.

More Related Videos

Analysis of Multidimensional Microscopy Data Using Cell-ACDC
06:17

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Published on: November 7, 2025

Guidelines and Experience Using Imaging Biomarker Explorer (IBEX) for Radiomics
10:17

Guidelines and Experience Using Imaging Biomarker Explorer (IBEX) for Radiomics

Published on: January 8, 2018

Related Experiment Videos

Last Updated: May 24, 2026

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification (ADCI) and Dose Estimation
10:33

Expedited Radiation Biodosimetry by Automated Dicentric Chromosome Identification (ADCI) and Dose Estimation

Published on: September 4, 2017

Analysis of Multidimensional Microscopy Data Using Cell-ACDC
06:17

Analysis of Multidimensional Microscopy Data Using Cell-ACDC

Published on: November 7, 2025

Guidelines and Experience Using Imaging Biomarker Explorer (IBEX) for Radiomics
10:17

Guidelines and Experience Using Imaging Biomarker Explorer (IBEX) for Radiomics

Published on: January 8, 2018

Area of Science:

  • Medical Imaging Informatics
  • Radiology Research
  • Biomedical Data Management

Background:

  • Digital Imaging and Communications in Medicine (DICOM) is the primary standard for medical imaging.
  • Clinical DICOM data often requires modification for research and clinical trial applications.
  • Existing tools may not adequately support specialized research imaging workflows.

Purpose of the Study:

  • To introduce DicomBrowser, a software solution for adapting clinical DICOM data for research.
  • To provide a flexible platform for modifying DICOM metadata to meet research imaging needs.
  • To streamline the transition from clinical to research-oriented DICOM data handling.

Main Methods:

  • Interactive loading and viewing of DICOM images and metadata across studies.
  • Flexible metadata modification via graphical user interface, scripting, or guided automation.
  • Saving modified DICOM objects locally or transmitting via C-STORE protocol.

Main Results:

  • DicomBrowser offers multiple approaches for DICOM metadata manipulation.
  • The software supports both ad hoc changes and batch processing for efficiency.
  • Modified DICOM data can be readily saved or shared within a network.

Conclusions:

  • DicomBrowser effectively bridges the gap between clinical DICOM standards and research imaging requirements.
  • The software provides a versatile and user-friendly environment for DICOM data adaptation.
  • Open-source availability promotes wider adoption in research settings.