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

7.5K
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...
7.5K
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

869
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...
869

You might also read

Related Articles

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

Sort by
Same author

Theoretical Prediction of Bias in Model-Based Material Decomposition.

Proceedings of SPIE--the International Society for Optical Engineering·2026
Same author

One-Step Material Decomposition Using Spectral Diffusion Posterior Sampling in Sparse-View Dual-Layer CT.

Proceedings of SPIE--the International Society for Optical Engineering·2026
Same author

Joint Estimation of Scatter Distribution and Material Maps in Volumetric Dual-Layer Cone-Beam CT.

Proceedings of SPIE--the International Society for Optical Engineering·2026
Same author

Evaluation of Fluence Reduction versus Sparsity for Diffusion Posterior Sampling Reconstruction in Low-Dose CT.

Proceedings of SPIE--the International Society for Optical Engineering·2026
Same author

Diffusion Posterior Sampling for Tomographic Reconstruction with Mixed Resolution Priors.

Proceedings of SPIE--the International Society for Optical Engineering·2026
Same author

Assessing the impact of CT reconstruction kernel on radiomic features extracted from normal and fibrotic tissue in patients with diffuse lung disease.

Proceedings of SPIE--the International Society for Optical Engineering·2026

Related Experiment Video

Updated: Apr 23, 2026

Construction of a Preclinical Multimodality Phantom Using Tissue-mimicking Materials for Quality Assurance in Tumor Size Measurement
06:33

Construction of a Preclinical Multimodality Phantom Using Tissue-mimicking Materials for Quality Assurance in Tumor Size Measurement

Published on: July 29, 2013

10.7K

Using a Physics-Based Approach to Standardize Radiomics Values: Experimental Validation in an Anthropomorphic Phantom

Huay Din1, Yijie Yuan2, Grace Hyun Kim3

  • 1Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.

Proceedings of Spie--The International Society for Optical Engineering
|April 22, 2026
PubMed
Summary
This summary is machine-generated.

This study developed a novel framework to standardize radiomics features, improving model reproducibility across different CT imaging systems. The method effectively reduces variations caused by imaging parameters, enhancing the reliability of quantitative imaging analysis.

Keywords:
GLCMGLRLMHistogramRadiomicsharmonizationstandardizationwavelet

More Related Videos

Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform
07:57

Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform

Published on: March 24, 2022

2.2K
Clinical Imaging of Microwave Mammography
05:28

Clinical Imaging of Microwave Mammography

Published on: November 14, 2025

436

Related Experiment Videos

Last Updated: Apr 23, 2026

Construction of a Preclinical Multimodality Phantom Using Tissue-mimicking Materials for Quality Assurance in Tumor Size Measurement
06:33

Construction of a Preclinical Multimodality Phantom Using Tissue-mimicking Materials for Quality Assurance in Tumor Size Measurement

Published on: July 29, 2013

10.7K
Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform
07:57

Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform

Published on: March 24, 2022

2.2K
Clinical Imaging of Microwave Mammography
05:28

Clinical Imaging of Microwave Mammography

Published on: November 14, 2025

436

Area of Science:

  • Medical Imaging
  • Radiology
  • Quantitative Imaging

Background:

  • Radiomics analysis is limited by feature variability due to different imaging systems.
  • Reproducible and generalizable radiomics models are crucial for clinical applications.

Purpose of the Study:

  • To evaluate a novel framework for standardizing radiomics features.
  • To assess the method's effectiveness on CT data across various imaging conditions.

Main Methods:

  • Applied a standardization framework to CT data from an anthropomorphic phantom.
  • Tested on data acquired at five dose levels and reconstructed with eight kernels.
  • Standardized radiomics features from histogram, GLCM, GLRLM, and wavelet transform classes.

Main Results:

  • Standardized features showed improved accuracy compared to unstandardized features (factor of three difference).
  • Standardization effectiveness was consistent across different dose levels.
  • Standardizing from smoother to sharper kernels presented greater challenges.

Conclusions:

  • The proposed method effectively standardizes radiomics features across diverse CT imaging conditions.
  • This standardization enhances the reproducibility and generalizability of radiomics models.
  • The framework shows promise for robust quantitative imaging in clinical CT settings.