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

686
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...
686
Vector Algebra: Method of Components01:08

Vector Algebra: Method of Components

18.7K
It is cumbersome to find the magnitudes of vectors using the parallelogram rule or using the graphical method to perform mathematical operations like addition, subtraction, and multiplication. There are two ways to circumvent this algebraic complexity. One way is to draw the vectors to scale, as in navigation, and read approximate vector lengths and angles (directions) from the graphs. The other way is to use the method of components.
In many applications, the magnitudes and directions of...
18.7K
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

1.1K
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
1.1K
Deconvolution01:20

Deconvolution

541
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
541
Block Diagram Reduction01:22

Block Diagram Reduction

526
The process of deriving the transfer function of a control system often involves reducing its block diagram to a single block. This simplification can be achieved through a series of strategic operations, including relocating branch points and comparators. These operations preserve the overall function of the system while allowing for easier manipulation and combination of blocks.
The first step in this process is the identification and relocation of a branch point. A branch point, where a...
526
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

284
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
284

You might also read

Related Articles

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

Sort by
Same author

Nonperiodic dynamic CT reconstruction using backward-warping implicit neural representation with diffeomorphism regularization<sup></sup>.

Physics in medicine and biology·2026
Same author

Disentangled deep learning method for interior tomographic reconstruction of low-dose x-ray CT.

Physics in medicine and biology·2025
Same author

PWLS-SOM: alternative PWLS reconstruction for limited-view CT by strategic optimization of a deep learning model.

Physics in medicine and biology·2025
Same author

ComptoNet: a Compton-map guided deep learning framework for multi-scatter estimation in multi-source stationary CT.

Physics in medicine and biology·2025
Same author

A geometric calibration method for a multi-segment static CT based on ordered subsets of sources and detectors.

Biomedical physics & engineering express·2025
Same author

Exploring charge sharing compensation using inter-pixel coincidence counters for photon counting detectors by deep-learning from local information.

Physics in medicine and biology·2024
Same journal

Effective contrast-enhanced preprocessing for intracranial artery segmentation in digital subtraction angiography.

Physics in medicine and biology·2026
Same journal

Improving Plan Quality in Adaptive Proton Therapy Using an Interactive Dose Modification Tool.

Physics in medicine and biology·2026
Same journal

Technical Note: Real-Time MLC Control and Latency Measurement Optimization with External Verification.

Physics in medicine and biology·2026
Same journal

Fetus-Specific Hematopoietic Stem Cell Dosimetry Framework for Leukemia-Relevant Target Cells During Prenatal Development.

Physics in medicine and biology·2026
Same journal

Deep learning-based dose prediction to enhance planning efficiency in cervical brachytherapy with hybrid applicators.

Physics in medicine and biology·2026
Same journal

Corrigendum: Referenceless MR thermometry-a comparison of five methods (2017<i>Phys. Med. Biol</i>.<b>62</b>1-16).

Physics in medicine and biology·2026
See all related articles

Related Experiment Video

Updated: Jan 15, 2026

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

A novel reconstruction method based on basis function decomposition for snapshot CAXRDT system.

Shengzi Zhao1,2, Le Shen1,2, Donghang Miao1,2

  • 1Department of Engineering Physics, Tsinghua University, 100084 Beijing, People's Republic of China.

Physics in Medicine and Biology
|January 13, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a new method for X-ray diffraction tomography (XRDT) reconstruction, improving accuracy by analyzing X-ray diffraction (XRD) patterns. The basis-function-decomposition reconstruction (BFD-Recon) method enhances image quality and suppresses noise in medical and security imaging.

Keywords:
basis function representationcoded apertureiterative reconstructionx-ray diffraction tomography

More Related Videos

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

732
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

668

Related Experiment Videos

Last Updated: Jan 15, 2026

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
Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique
04:48

Swin-PSAxialNet: An Efficient Multi-Organ Segmentation Technique

Published on: July 5, 2024

732
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

668

Area of Science:

  • Materials Science
  • Medical Imaging
  • Computational Imaging

Background:

  • X-ray diffraction (XRD) provides molecular structural information, with applications in medical diagnostics and security.
  • Snapshot coded aperture XRDT (SCA-XRDT) offers fast scanning but faces reconstruction challenges due to ill-posed problems and poor data conditions.
  • Accurate image reconstruction is crucial for reliable analysis in SCA-XRDT applications.

Purpose of the Study:

  • To develop an improved iterative reconstruction algorithm for SCA-XRDT by incorporating inherent characteristics of XRD patterns.
  • To enhance the accuracy and performance of XRDT image reconstruction by addressing data conditions and ill-posedness.
  • To introduce a novel basis-function-decomposition reconstruction (BFD-Recon) method for SCA-XRDT.

Main Methods:

  • Analyzed physical factors influencing XRD patterns to represent them as linear combinations of basis functions.
  • Developed the BFD-Recon method, integrating basis function representation as a prior into a model-based SCA-XRDT framework.
  • Utilized the Split Bregman algorithm for iterative optimization, imposing smoothness and sparsity constraints on basis function parameters.

Main Results:

  • BFD-Recon achieved more accurate reconstruction of XRD patterns, particularly sharp peaks, compared to conventional methods.
  • The method effectively suppressed noise and background signal interference in reconstructed XRD patterns.
  • BFD-Recon increased correlation coefficients by up to 10% and average PSNR by 20% against ground truth.

Conclusions:

  • The proposed basis function decomposition method is effective and generally applicable for XRD patterns.
  • Integrating basis-function-decomposition into model-based iterative reconstruction significantly enhances XRDT performance.
  • BFD-Recon alleviates reconstruction ill-posedness by reducing unknowns and providing prior information, improving spectral dimension value.