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

Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

856
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...
856
Aliasing01:18

Aliasing

805
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...
805
Fast Fourier Transform01:10

Fast Fourier Transform

1.2K
The Fast Fourier Transform (FFT) is a computational algorithm designed to compute the Discrete Fourier Transform (DFT) efficiently. By breaking down the calculations into smaller, manageable sections, the FFT significantly reduces the computational complexity involved. Direct computation of an N-point DFT requires N2 complex multiplications, whereas the FFT algorithm needs only (N/2)log⁡2N multiplications, offering a much faster performance.
The computational efficiency of the FFT becomes...
1.2K

You might also read

Related Articles

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

Sort by
Same author

Antagonism of β-klotho signaling by peptide 19 impairs wheel running in male mice and potentiates the cisplatin-induced decrease in wheel running.

Frontiers in pharmacology·2026
Same author

Precision prebiotics: Engineering food-derived polysaccharides to target specific SCFA-producing taxa for neuroprotection via the microbiota-gut-brain axis.

Current research in food science·2026
Same author

A knowledge-guided deep learning framework for quantitative nucleic acid testing.

Briefings in bioinformatics·2026
Same author

DyMamba: dynamic Mamba for microscopy image semantic segmentation.

Bioinformatics (Oxford, England)·2026
Same author

Earthworm-Inspired Self-Powered Multistimuli Neuromorphic Vision Skin with Homogeneous Ion Heterogel Arrays.

ACS applied materials & interfaces·2026
Same author

Correction: Study on the mechanism of 18β-glycyrrhetinic acid inhibiting the proliferation of renal cancer cells by inducing autophagy through the miR-27a-5p/LC3 axis.

Frontiers in oncology·2026

Related Experiment Video

Updated: Apr 3, 2026

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
10:44

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

Published on: June 21, 2024

1.4K

FASART: An iterative reconstruction algorithm with inter-iteration adaptive NAD filter.

Ziying Zhou1, Yugang Li1, Fa Zhang2

  • 1Beijing Lab of Intelligent Information Technology, School of Computer Science, Beijing Institute of Technology, Beijing 100081, China.

Bio-Medical Materials and Engineering
|September 26, 2015
PubMed
Summary
This summary is machine-generated.

Electron tomography (ET) reconstruction struggles with noisy, incomplete data. A new adaptive method (FASART) effectively reduces noise while preserving crucial structural details in biological imaging.

Keywords:
3D reconstructionelectron tomography (ET)iterative methodnon-linear anisotropic diffusion (NAD) filter

More Related Videos

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
06:25

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

8.9K
Author Spotlight: Revolutionizing Remote Surgery with Augmented Reality and Robotics for Enhanced Precision and Accessibility
07:46

Author Spotlight: Revolutionizing Remote Surgery with Augmented Reality and Robotics for Enhanced Precision and Accessibility

Published on: August 9, 2024

1.2K

Related Experiment Videos

Last Updated: Apr 3, 2026

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging
10:44

Three-Dimensional Phase Resolved Functional Lung Magnetic Resonance Imaging

Published on: June 21, 2024

1.4K
Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
06:25

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

8.9K
Author Spotlight: Revolutionizing Remote Surgery with Augmented Reality and Robotics for Enhanced Precision and Accessibility
07:46

Author Spotlight: Revolutionizing Remote Surgery with Augmented Reality and Robotics for Enhanced Precision and Accessibility

Published on: August 9, 2024

1.2K

Area of Science:

  • Biophysics
  • Microscopy
  • Image Reconstruction

Background:

  • Electron tomography (ET) is vital for visualizing large biological structures.
  • Current reconstruction methods fail with noisy and incomplete projection data.
  • Accurate reconstruction is crucial for understanding cellular and molecular architecture.

Purpose of the Study:

  • To introduce a novel iterative reconstruction method for electron tomography.
  • To address limitations of existing methods in handling noisy and incomplete datasets.
  • To improve the preservation of structural details during image reconstruction.

Main Methods:

  • Developed an adaptive simultaneous algebraic reconstruction technique (FASART).
  • Integrated an inter-iteration adaptive non-linear anisotropic diffusion (NAD) filter.
  • Optimized filter parameters for enhanced noise suppression and detail preservation.

Main Results:

  • FASART effectively restrains noise during iterative reconstruction.
  • The method successfully preserves fine details of structure edges.
  • Experimental results demonstrate superior performance over existing techniques.

Conclusions:

  • FASART offers a robust solution for electron tomography reconstruction with challenging data.
  • The NAD filter integration significantly enhances image quality and structural fidelity.
  • This method advances the capability of ET for high-resolution biological structure analysis.