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

Orthogonal Trajectories01:26

Orthogonal Trajectories

Orthogonal trajectories describe the geometric relationship between two families of curves that intersect each other at right angles. One illustrative case involves a family of parabolas that open sideways along the x-axis. These curves share a common shape but differ by a scaling parameter, resulting in a set of curves that all pass through the origin and widen at different rates.Determining Orthogonal TrajectoriesTo identify the orthogonal trajectories for these parabolas, the first step...
Real-World Applications of Space Curves01:29

Real-World Applications of Space Curves

Modern aerospace navigation depends on the accurate prediction of motion in three-dimensional space. In defense applications, radar systems continuously track both interceptors and moving aerial targets to find whether their flight paths will result in a collision. These motions are modeled mathematically as space curves, which represent paths that change continuously with time. Each object’s position is described by a vector function that specifies its location in terms of time-dependent...
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...
State Space Representation01:27

State Space Representation

The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
Curvilinear Motion: Rectangular Components01:23

Curvilinear Motion: Rectangular Components

Curvilinear motion characterizes the movement of a particle or object along a curved path, notably evident when envisioning a car navigating a winding road. If the car starts at point A, its position vector is established within a fixed frame of reference, where the ratio of the position vector to its magnitude signifies the unit vector pointing in the position vector's direction.
As the car advances, its position evolves over time. Quantifying the car's velocity involves computing the time...
Residuals and Least-Squares Property01:11

Residuals and Least-Squares Property

The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...

You might also read

Related Articles

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

Sort by
Same author

The contribution of apical stimulation to Mandarin speech perception in users of the MED-EL COMBI 40+ cochlear implant.

Acta oto-laryngologica·2010
Same author

[Scapular belt for the treatment of comminuted fractures of scapula].

Zhongguo gu shang = China journal of orthopaedics and traumatology·2010
Same author

Manipulation of ordered nanostructures of protonated polyoxometalate through covalently bonded modification.

Chemistry (Weinheim an der Bergstrasse, Germany)·2010
Same author

Developments in nonsteroidal antiandrogens targeting the androgen receptor.

ChemMedChem·2010
Same author

Dynamic presentation of immobilized ligands regulated through biomolecular recognition.

Journal of the American Chemical Society·2010
Same author

[Research on crop-weed discrimination using a field imaging spectrometer].

Guang pu xue yu guang pu fen xi = Guang pu·2010

Related Experiment Video

Updated: Jul 3, 2026

Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

A statistical approach to SENSE regularization with arbitrary k-space trajectories.

Leslie Ying1, Bo Liu, Michael C Steckner

  • 1Department of Electrical Engineering and Computer Science, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin 53211, USA. leiying@uwm.edu

Magnetic Resonance in Medicine
|July 31, 2008
PubMed
Summary
This summary is machine-generated.

This study introduces adaptive Huber regularization to improve SENSE MRI reconstruction. The new method enhances image quality and speeds up convergence without increasing computation time.

More Related Videos

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis
06:44

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis

Published on: September 23, 2025

Related Experiment Videos

Last Updated: Jul 3, 2026

Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis
06:44

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis

Published on: September 23, 2025

Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Image Reconstruction
  • Regularization Techniques

Background:

  • SENSE reconstruction in MRI faces signal-to-noise ratio (SNR) degradation due to ill-conditioning, especially at higher reduction factors.
  • This ill-conditioning negatively impacts the convergence of iterative reconstruction methods like the conjugate gradient method.
  • Existing regularization methods, such as Tikhonov and Total Variation (TV), have limitations like blurry edges or blocky artifacts.

Purpose of the Study:

  • To develop a novel adaptive regularization method for SENSE MRI reconstruction.
  • To address the ill-conditioning problem and improve image quality and reconstruction speed.
  • To overcome the limitations of existing regularization techniques.

Main Methods:

  • A new adaptive regularization method based on maximum a posteriori (MAP) statistical estimation was developed.
  • A Huber Markov random field prior was utilized, incorporating image and noise statistics for adaptive control.
  • The proposed adaptive Huber regularization was compared against unregularized conjugate gradient and Tikhonov regularization.

Main Results:

  • The adaptive Huber regularization effectively mitigated the ill-conditioning problem in SENSE reconstruction.
  • Improved image quality was observed, addressing issues like blurry edges and blocky artifacts.
  • Enhanced convergence speed was achieved in both phantom and in vivo experiments.

Conclusions:

  • The proposed adaptive Huber regularization offers a superior approach for SENSE MRI reconstruction.
  • This method significantly improves image quality and reconstruction efficiency over traditional techniques.
  • The adaptive regularization strategy provides a robust solution for challenging MRI reconstruction scenarios.