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

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)01:20

¹³C NMR: Distortionless Enhancement by Polarization Transfer (DEPT)

1.0K
When proton-coupled carbon-13 spectra are simplified by a broadband proton decoupling technique, structural information about the coupled protons is lost. Distortionless enhancement by polarization transfer (DEPT) is a technique that provides information on the number of hydrogens attached to each carbon in a molecule. While the DEPT experiment utilizes complex pulse sequences, the pulse delay and flip angle are specifically manipulated. The resulting signals have different phases depending on...
1.0K
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

167
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
167
¹³C NMR: ¹H–¹³C Decoupling01:04

¹³C NMR: ¹H–¹³C Decoupling

1.0K
The probability of having two carbon-13 atoms next to each other is negligible because of the low natural abundance of carbon-13. Consequently, peak splitting due to carbon-carbon spin-spin coupling is not observed in spectra. However, protons up to three sigma bonds away split the carbon signal according to the n+1 rule, resulting in complicated spectra.
A broadband decoupling technique is used to simplify these complex, sometimes overlapping, signals. Broadband decoupling relies on a...
1.0K
Aliasing01:18

Aliasing

117
Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
If the sampling frequency is below the Nyquist rate, these replicas overlap, preventing the original...
117

You might also read

Related Articles

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

Sort by
Same author

Low-complexity reconstruction of low-dose spectral CT via double low-rank tensor factorization with adaptive transforms.

Medical image analysis·2026
Same author

Segmentation-Guided Accelerating Diffusion Model for Cardiac CT Motion Artifact Reduction via Limited-Angle Imaging.

IEEE transactions on medical imaging·2026
Same author

Multi-granularity Adversarial Generation Integrated Consistency Representation for Chest Low-Contrast-Enhanced CT Synthesis.

IEEE transactions on medical imaging·2026
Same author

FDA-Recon: Feature and data alignment reconstruction for sparse-view CBCT.

Medical image analysis·2026
Same author

WOADNet: A Wavelet-Inspired Orientational Adaptive Dictionary Network for CT Metal Artifact Reduction.

IEEE journal of biomedical and health informatics·2025
Same author

Hybrid plug-and-play CT image restoration using nonconvex low-rank group sparsity and deep denoiser priors.

Physics in medicine and biology·2024
Same journal

Facial iPPG heatmap patterns based on period-aware autoencoder show association with carotid atherosclerosis towards non-contact hemodynamic assessment.

Computer methods and programs in biomedicine·2026
Same journal

Explainable machine learning models predict liver fibrosis risk and outcome in the general population: Development and multi-cohort external validation.

Computer methods and programs in biomedicine·2026
Same journal

Evaluation of surrogate endpoints for survival outcomes using the surrogate package in R.

Computer methods and programs in biomedicine·2026
Same journal

Relative spectral and frication-based descriptors as numerical indicators of place of articulation shifts in fricatives produced by Polish children.

Computer methods and programs in biomedicine·2026
Same journal

Leaflet resection improves valve expansion and hemodynamic performance in redo TAVI with balloon- and self-expanding transcatheter heart valve configurations.

Computer methods and programs in biomedicine·2026
Same journal

Spectral super-resolution for Parkinson's voice via representation-level methods under mixed-reality acquisition.

Computer methods and programs in biomedicine·2026
See all related articles

Related Experiment Video

Updated: Jun 2, 2025

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
17:06

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

26.1K

DECT sparse reconstruction based on hybrid spectrum data generative diffusion model.

Jin Liu1, Fan Wu2, Guorui Zhan2

  • 1College of Computer and Information, Anhui Polytechnic University, Wuhu, China; Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education, Nanjing, China.

Computer Methods and Programs in Biomedicine
|January 14, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a hybrid spectrum data generative diffusion reconstruction model (HSGDM) to enhance sparse view dual-energy computed tomography (DECT) imaging quality. The novel approach improves image precision and detail preservation while reducing radiation dose.

Keywords:
DECTDiffusion modelSparse view reconstructionWavelet space

More Related Videos

Digital Inline Holographic Microscopy DIHM of Weakly-scattering Subjects
10:16

Digital Inline Holographic Microscopy DIHM of Weakly-scattering Subjects

Published on: February 8, 2014

12.2K
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
09:33

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

28.4K

Related Experiment Videos

Last Updated: Jun 2, 2025

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
17:06

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

26.1K
Digital Inline Holographic Microscopy DIHM of Weakly-scattering Subjects
10:16

Digital Inline Holographic Microscopy DIHM of Weakly-scattering Subjects

Published on: February 8, 2014

12.2K
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
09:33

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

28.4K

Area of Science:

  • Medical Imaging
  • Computational Imaging
  • Image Reconstruction

Background:

  • Dual-energy computed tomography (DECT) offers material differentiation but faces challenges with radiation exposure.
  • Sparse view DECT imaging reduces radiation dose but can compromise image quality.
  • Existing reconstruction methods struggle to balance image quality and radiation dose in DECT.

Purpose of the Study:

  • To develop a novel reconstruction model for sparse view DECT imaging.
  • To improve image quality in DECT while minimizing radiation exposure.
  • To address the trade-off between image quality and radiation dose in DECT.

Main Methods:

  • A hybrid spectrum data generative diffusion reconstruction model (HSGDM) was developed.
  • The model leverages spectral similarity using interleaved angles for sparse scanning.
  • It employs a hybrid constraint integrating image and wavelet space diffusion models for iterative reconstruction.

Main Results:

  • The HSGDM achieved competitive precision in CT values, detail preservation, and artifact elimination.
  • Reconstruction with 30 sparse views showed significant improvements in PSNR, SSIM, and FID scores.
  • Ablation studies confirmed the effectiveness of the hybrid prior combining image and wavelet space modules.

Conclusions:

  • A unified, optimized mathematical model integrating image and wavelet space priors was developed.
  • The proposed HSGDM offers a practical and interpretable solution for sparse DECT reconstruction.
  • Experimental results validate the model's superior performance in sparse DECT imaging.