Related Experiment Video
Updated: Jul 13, 2026

06:25
Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
Published on: February 12, 2014
Improved k-space trajectory measurement with signal shifting
Marine Beaumont1,2, Laurent Lamalle3, Christoph Segebarth1,2
1Institut National de la Santé et de la Recherche Médicale (INSERM) U836, Grenoble, France.
Magnetic Resonance in Medicine
|July 31, 2007
Summary
This study introduces a faster k-space trajectory measurement method for high-resolution imaging. A novel dephasing gradient technique improves signal accuracy without extending scan times.
Area of Science:
- Magnetic Resonance Imaging (MRI)
- Medical Physics
- Image Acquisition
Background:
- Accurate k-space trajectory measurement is crucial for MRI.
- Existing methods like self-encoding are time-consuming.
- Localized slice methods are faster but have limitations for high-resolution imaging.
Purpose of the Study:
- To develop a faster and more accurate k-space trajectory measurement technique.
- To address signal drop-off issues at the k-space periphery in high-resolution MRI.
- To improve the estimation of MRI trajectories without significantly increasing acquisition time.
Main Methods:
- Proposed a novel approach using an additional dephasing gradient.
- Applied the dephasing gradient before the measured gradient to shift the signal maximum.
- Evaluated the method in the context of high spatial resolution experiments.
Main Results:
- The new method effectively overcomes signal drop-off at high k-space frequencies.
- Improved accuracy in estimating k-space trajectories, especially at the periphery.
- Achieved this improvement without substantially increasing measurement duration compared to localized slice methods.
Conclusions:
- The proposed dephasing gradient technique offers a faster and more accurate solution for k-space trajectory measurement in high-resolution MRI.
- This advancement can enhance image quality and reduce scan times in demanding MRI applications.
- The method provides a practical solution to a known limitation in MRI trajectory estimation.
Related Concept Videos
Basic Operations on Signals
Basic signal operations include time reversal, time scaling, time shifting, and amplitude transformations. These operations are fundamental in signal processing and analysis.
Time Reversal mirrors a continuous-time signal about the vertical axis at t=0. This is achieved by substituting t with −t. For example, if a signal x(t) is considered, the time-reversed signal is x(−t). This operation can be graphically represented, showing the mirrored signal.
Time Reversal mirrors a continuous-time signal about the vertical axis at t=0. This is achieved by substituting t with −t. For example, if a signal x(t) is considered, the time-reversed signal is x(−t). This operation can be graphically represented, showing the mirrored signal.
Reconstruction of Signal using Interpolation
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 sampling...
Distance Measurements by Taping
Tapes are essential in surveying for accurate, durable, and short-distance measurements. Made from lightweight, nylon-coated steel, they offer flexibility and strength for rugged outdoor use. The nylon coating protects against rust and wear, extending the tape's life. Standard lengths, around 30 meters, are marked in meters and millimeters for precision.Surveyors select tapes based on site conditions and accuracy needs. Lightweight, nylon-coated tapes are commonly used for ease of handling and...
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...
Properties of DTFT I
In signal processing, Discrete-Time Fourier Transforms (DTFTs) play a critical role in analyzing discrete-time signals in the frequency domain. Various properties of the DTFTs such as linearity, time-shifting, frequency-shifting, time reversal, conjugation, and time scaling help understand and manipulate these signals for different applications.
The linearity property of DTFTs is fundamental. If two discrete-time signals are multiplied by constants a and b respectively, and then combined to...
The linearity property of DTFTs is fundamental. If two discrete-time signals are multiplied by constants a and b respectively, and then combined to...
Doppler Effect - II
The Doppler effect has several practical, real-world applications. For instance, meteorologists use Doppler radars to interpret weather events based on the Doppler effect. Typically, a transmitter emits radio waves at a specific frequency toward the sky from a weather station. The radio waves bounce off the clouds and precipitation and travel back to the weather station. The radio frequency of the waves reflected back to the station appears to decrease if the clouds or precipitation are moving...

