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

Area Problem01:26

Area Problem

Determining the area of a region with straight edges is straightforward, as geometric formulas for rectangles, triangles, and polygons can be applied directly. However, traditional geometric methods are insufficient when a region has a curved boundary, such as the area under a function.fromThe area problem involves finding a systematic way to measure such regions. One approach to solving this problem is through approximation. Instead of attempting to compute the area exactly at the outset, the...
Linear Approximations01:23

Linear Approximations

For a differentiable function of two variables, linear approximation estimates values near a known point by replacing the curved surface with its tangent plane. Consider the function\begin{equation*}f(x,y)=x^2+3y^2\end{equation*}near the point (2, 1). The exact value at this point is f(2, 1) = 22 + 3(1)2 = 4 + 3 = 7.The linear approximation of f(x, y)) near (a, b) is\begin{equation*}L(x,y)=f(a,b)+f_x(a,b)(x-a)+f_y(a,b)(y-b)\end{equation*}First, compute the partial derivatives: fx(x, y) = 2x and...
Region of Convergence of Laplace Tarnsform01:20

Region of Convergence of Laplace Tarnsform

The Region of Convergence (ROC) is a fundamental concept in signal processing and system analysis, particularly associated with the Laplace transform. The ROC represents an area in the complex plane where the Laplace transform of a given signal converges, determining the transform's applicability and utility.
Consider a decaying exponential signal that begins at a specific time. When deriving its Laplace transform, the time-domain variable is replaced with a complex variable. This substitution...
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

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...
Area Computation by the Alternative Coordinate Method01:24

Area Computation by the Alternative Coordinate Method

The alternative coordinate method, also known as the Shoelace Formula, is a technique for determining the area of a traverse using Cartesian coordinates. This method relies on the sequential arrangement of x and y coordinates for each point of the shape, ensuring accuracy and ease of application.In this approach, each corner's x and y coordinates are listed as fractions, with the x-coordinate as the numerator and the y-coordinate as the denominator. These coordinates are arranged sequentially...
Linearization and Approximation01:26

Linearization and Approximation

Linearization is a mathematical technique used to approximate complex, nonlinear functions with simpler linear models in the vicinity of a chosen reference point. The method is based on the idea that, although a function may be difficult to evaluate exactly, its behavior near a specific input value can often be closely approximated by the tangent line at that point. This approach is particularly useful when small deviations from a known value are involved.Consider the square root function, for...

You might also read

Related Articles

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

Sort by
Same author

Prognostic Value of Preoperative Peak Expiratory Flow to Predict Postoperative Pulmonary Complications in Surgical Lung Cancer Patients.

Frontiers in oncology·2021
Same author

Safety and Feasibility of Video-Assisted Thoracoscopic Day Surgery and Inpatient Surgery in Patients With Non-small Cell Lung Cancer: A Single-Center Retrospective Cohort Study.

Frontiers in surgery·2021
Same author

Overexpression of MdASMT9, an N-acetylserotonin methyltransferase gene, increases melatonin biosynthesis and improves water-use efficiency in transgenic apple.

Tree physiology·2021
Same author

Simulating the impact of piers on hydrodynamics and pollutant transport: A case study in the Middle Yangtze River.

PloS one·2021
Same author

Hierarchical MXene/transition metal chalcogenide heterostructures for electrochemical energy storage and conversion.

Nanoscale·2021
Same author

Deciphering cell lineage specification of human lung adenocarcinoma with single-cell RNA sequencing.

Nature communications·2021
Same journal

Multi-Contrast Human Brain CEST MRI at 11.7 T: First In Vivo Demonstration.

Magnetic resonance in medicine·2026
Same journal

Suppression of Oscillation and Ghosting in RF-Spoiled Gradient-Echo-Based Dynamic Imaging.

Magnetic resonance in medicine·2026
Same journal

A Simple, Dynamic Geometric Phantom for MRI and CT Reconstruction Pipelines: Beyond Shepp-Logan.

Magnetic resonance in medicine·2026
Same journal

7T 3D-EPI PCASL With High SNR Efficiency and Robustness to Through-Plane B<sub>0</sub> Field Gradients.

Magnetic resonance in medicine·2026
Same journal

A Comparison of Tissue Property Values Estimated Using Conventional Cardiac MRF and MT-Cardiac MRF.

Magnetic resonance in medicine·2026
Same journal

Dependence of the Extra-Cellular Diffusion Coefficient on the Fractions of Neurites and Cell Bodies in Gray Matter.

Magnetic resonance in medicine·2026
See all related articles

Related Experiment Video

Updated: Jun 22, 2026

Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture
09:04

Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture

Published on: February 23, 2018

Reliable two-dimensional phase unwrapping method using region growing and local linear estimation.

Kun Zhou1, Maxim Zaitsev, Shanglian Bao

  • 1Beijing Key Laboratory of Medical Physics and Engineering, Peking University, Beijing, PR China.

Magnetic Resonance in Medicine
|July 3, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces a novel 2D phase unwrapping algorithm for Magnetic Resonance Imaging (MRI). The method effectively corrects phase wrapping in noisy images, improving MRI analysis.

More Related Videos

Quantifying Intermembrane Distances with Serial Image Dilations
07:45

Quantifying Intermembrane Distances with Serial Image Dilations

Published on: September 28, 2018

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

Related Experiment Videos

Last Updated: Jun 22, 2026

Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture
09:04

Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture

Published on: February 23, 2018

Quantifying Intermembrane Distances with Serial Image Dilations
07:45

Quantifying Intermembrane Distances with Serial Image Dilations

Published on: September 28, 2018

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

Area of Science:

  • Medical Imaging
  • Image Processing
  • Magnetic Resonance Imaging (MRI)

Background:

  • Phase maps in MRI offer valuable data on field inhomogeneity, blood flow velocity, and water-fat chemical shift.
  • Phase wrapping, due to the limited (-pi,pi] range of phase values, hinders accurate MRI analysis and interpretation.

Purpose of the Study:

  • To develop and validate a robust two-dimensional phase unwrapping algorithm for MRI.
  • To address the challenges posed by phase wrapping in noisy and complex phase data.

Main Methods:

  • A quality-guided region growing approach combined with local linear estimation for phase unwrapping.
  • Utilizing the variance of second-order partial derivatives of the phase as a quality criterion.
  • Employing phase information from unwrapped neighboring pixels for predictive phase correction via linear regression.

Main Results:

  • The algorithm demonstrated successful phase unwrapping on both simulated and real MRI data.
  • Effective correction of phase images corrupted by significant noise and rapid phase variations was achieved.

Conclusions:

  • The proposed 2D phase unwrapping algorithm enhances the reliability of MRI phase map analysis.
  • This technique offers a valuable tool for overcoming phase wrapping artifacts in diverse MRI applications.