Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Computed Tomography

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...

2D NMR: Heteronuclear Single-Quantum Correlation Spectroscopy (HSQC)

2D NMR: Heteronuclear Single-Quantum Correlation Spectroscopy (HSQC)

Heteronuclear single-quantum correlation spectroscopy (HSQC) is a 2D NMR technique that reveals one-bond correlations between hydrogen and a heteronucleus. The HSQC experiment is similar to the heteronuclear correlation experiment (HETCOR) but is more sensitive. In the HSQC spectrum, the proton chemical shift is plotted on the horizontal F2 axis, while the 13C chemical shift is plotted on the vertical F1 axis. The corresponding proton and 13C spectra are also shown. The HSQC contour plot does...

Imaging Studies III: Computed Tomography

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

Agreement of the modified Medical Research Council and New York Heart Association scales for assessing the impact of self-rated breathlessness in cardiopulmonary disease.

ERJ open research·2022

Same author

Minimal clinically important differences for Dyspnea-12 and MDP scores are similar at 2 weeks and 6 months: follow-up of a longitudinal clinical study.

The European respiratory journal·2020

Same author

Feasibility of unconstrained three-material decomposition: imaging an excised human heart using a prototype silicon photon-counting CT detector.

European radiology·2020

Same author

Minimal Clinically Important Differences and Feasibility of Dyspnea-12 and the Multidimensional Dyspnea Profile in Cardiorespiratory Disease.

Journal of pain and symptom management·2020

Same author

Erratum for "A Framework for Evaluating Threshold Variation Compensation Methods in Photon Counting Spectral CT".

IEEE transactions on medical imaging·2020

Same author

Validation of the Swedish Multidimensional Dyspnea Profile (MDP) in outpatients with cardiorespiratory disease.

BMJ open respiratory research·2019

Search research articles

Related Experiment Video

Updated: May 23, 2026

Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images

Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images

Published on: February 18, 2015

Synthetic Hounsfield units from spectral CT data.

Hans Bornefalk¹

¹Department of Physics, Royal Institute of Technology, SE-106 91 Stockholm, Sweden. hans.bornefalk@mi.physics.kth.se

Physics in Medicine and Biology

|March 22, 2012

Summary

Spectral CT can generate beam-hardening-free synthetic images with accurate CT numbers, maintaining radiologist familiarity. This approach aids the transition from conventional CT to advanced spectral CT imaging.

Area of Science:

Medical Imaging
Radiology
Image Reconstruction

Background:

Conventional CT (Computed Tomography) is being replaced by spectral CT.
Spectral CT offers advanced imaging capabilities but requires adaptation from radiologists.
Beam-hardening artifacts are a limitation in conventional CT.

Purpose of the Study:

To develop a method for creating synthetic images from spectral CT data.
To ensure these synthetic images have absolute CT numbers familiar to radiologists.
To facilitate the transition from conventional CT to spectral CT without relearning.

Main Methods:

Basis decomposition of spectral CT data.
Formation of 'dichromatic' images.
Generation of synthetic images with absolute CT numbers.

More Related Videos

Non-invasive Skeletal Muscle Quantification in Small Animals Using Micro-computed Tomography

Non-invasive Skeletal Muscle Quantification in Small Animals Using Micro-computed Tomography

Published on: November 8, 2024

Hybrid µCT-FMT imaging and image analysis

Hybrid µCT-FMT imaging and image analysis

Published on: June 4, 2015

Related Experiment Videos

Last Updated: May 23, 2026

Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images

Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images

Published on: February 18, 2015

Non-invasive Skeletal Muscle Quantification in Small Animals Using Micro-computed Tomography

Non-invasive Skeletal Muscle Quantification in Small Animals Using Micro-computed Tomography

Published on: November 8, 2024

Hybrid µCT-FMT imaging and image analysis

Hybrid µCT-FMT imaging and image analysis

Published on: June 4, 2015

Main Results:

Accurate CT numbers for all tissues were achieved in synthetic images.
The method successfully eliminated beam-hardening artifacts.
No additional image reconstruction was required.

Conclusions:

The proposed method enables the creation of beam-hardening-free synthetic images from spectral CT data.
These synthetic images retain familiar absolute CT numbers, easing radiologist adoption.
Presenting synthetic images alongside task-optimized reconstructions can further support the transition to spectral CT.