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

4.7K
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...
4.7K
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

30
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...
30

You might also read

Related Articles

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

Sort by
Same author

Prospective ECG-gated High-Pitch Photon-Counting CT Angiography: Evaluation of measurement accuracy for aortic annulus sizing in TAVR planning.

European journal of radiology·2024
Same author

Photon-counting detector CT improves quality of arterial phase abdominal scans: A head-to-head comparison with energy-integrating CT.

European journal of radiology·2022
Same author

Natural language processing of radiology reports to investigate the effects of the COVID-19 pandemic on the incidence and age distribution of fractures.

Skeletal radiology·2021
Same author

A Hybrid Reporting Platform for Extended RadLex Coding Combining Structured Reporting Templates and Natural Language Processing.

Journal of digital imaging·2020
Same author

Workflow-centred open-source fully automated lung volumetry in chest CT.

Clinical radiology·2019
Same author

Vaccinia-based oncolytic immunotherapy Pexastimogene Devacirepvec in patients with advanced hepatocellular carcinoma after sorafenib failure: a randomized multicenter Phase IIb trial (TRAVERSE).

Oncoimmunology·2019

Related Experiment Video

Updated: Aug 1, 2025

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography
07:01

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography

Published on: October 24, 2019

9.9K

Soft Reconstruction Kernels Improve HCC Imaging on a Photon-Counting Detector CT.

D Graafen1, L Müller1, M C Halfmann2

  • 1Diagnostic and Interventional Radiology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany (D.G., L.M., M.C.H., F.S., C.D., Y.Y., T.E., R.K.).

Academic Radiology
|April 24, 2023
PubMed
Summary
This summary is machine-generated.

Softer reconstruction kernels provide superior image quality for hepatocellular carcinoma (HCC) detection using photon-counting detector (PCD) CT. These kernels enhance noise reduction and overall image quality, crucial for non-invasive HCC diagnosis.

Keywords:
CT reconstruction kernelsHepatocellular carcinomaPhoton-counting detector CT

More Related Videos

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph
05:32

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph

Published on: February 21, 2025

351
X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging
08:30

X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging

Published on: September 11, 2011

14.5K

Related Experiment Videos

Last Updated: Aug 1, 2025

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography
07:01

3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography

Published on: October 24, 2019

9.9K
Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph
05:32

Retrospective Cardiac Gating with A Prototype Small-Animal X-ray Computed Tomograph

Published on: February 21, 2025

351
X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging
08:30

X-ray Dose Reduction through Adaptive Exposure in Fluoroscopic Imaging

Published on: September 11, 2011

14.5K

Area of Science:

  • Medical Imaging
  • Radiology
  • Oncology

Background:

  • Hepatocellular carcinoma (HCC) diagnosis relies heavily on imaging quality.
  • Photon-counting detector (PCD) CT offers enhanced image quality through noise reduction and higher spatial resolution.
  • PCD CT inherently provides spectral information, aiding in diagnosis.

Purpose of the Study:

  • To evaluate image quality improvements for HCC imaging using triple-phase liver PCD CT.
  • To identify the optimal reconstruction kernel for HCC detection with PCD CT.
  • To compare objective and subjective image quality metrics across different reconstruction kernels.

Main Methods:

  • Phantom experiments analyzed objective quality characteristics of reconstruction kernels at various sharpness levels.
  • 24 patients with viable HCC lesions underwent triple-phase liver PCD CT.
  • Virtual monoenergetic images were reconstructed using different kernels; quantitative (CNR, edge sharpness) and qualitative (noise, contrast, lesion conspicuity, overall quality) analyses were performed.

Main Results:

  • Softer reconstruction kernels (sharpness level 36) yielded the highest contrast-to-noise ratio (CNR) in all contrast phases (p < 0.05).
  • Softer kernels were qualitatively rated superior for noise and overall image quality (p < 0.05).
  • No significant differences were observed in lesion sharpness, image contrast, or lesion conspicuity between kernel types.

Conclusions:

  • Soft reconstruction kernels provide the best overall image quality for evaluating HCC with PCD CT.
  • Quantitative kernels offer comparable image quality to regular body kernels and should be preferred due to spectral post-processing potential.
  • Optimal kernel selection is critical for maximizing diagnostic accuracy in HCC imaging with PCD CT.