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

Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

10.1K
Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
10.1K
Assessment of Diffusion and Perfusion01:17

Assessment of Diffusion and Perfusion

1.9K
Understanding and evaluating diffusion and perfusion is critical in assessing a patient's respiratory and circulatory health. These processes play key roles in maintaining the body's internal environment, ensuring that tissues receive adequate oxygen while waste products are efficiently removed.
The Role of Diffusion in Respiration
Diffusion is the process by which molecules move from an area of higher concentration to an area of lower concentration. In the respiratory system, this...
1.9K

You might also read

Related Articles

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

Sort by
Same author

Risk Factors for Diabetic Foot Ulcers and the Role of Thermal Imaging in Early Detection.

Cureus·2026
Same author

An Evaluation of the Effect of Dimple Insoles on Foot Temperature in Diabetic Patients.

Sensors (Basel, Switzerland)·2025
Same author

Phase quantification using deep neural network processing of XRD patterns.

IUCrJ·2024
Same author

Cam-Unet: Print-Cam Image Correction for Zero-Bit Fourier Image Watermarking.

Sensors (Basel, Switzerland)·2024
Same author

Tracking online low-rank approximations of higher-order incomplete streaming tensors.

Patterns (New York, N.Y.)·2023
Same author

Magnetic-Field-Based Indoor Positioning Using Temporal Convolutional Networks.

Sensors (Basel, Switzerland)·2023

Related Experiment Video

Updated: Mar 13, 2026

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
09:33

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

29.4K

Analytical performance bounds for multi-tensor diffusion-MRI.

Farid Ahmed Sid1, Karim Abed-Meraim2, Rachid Harba2

  • 1ParIMéd/LRPE, FEI, USTHB, BP 32 El Alia, Bab Ezzouar, 16111, Algiers, Algeria.

Magnetic Resonance Imaging
|October 17, 2016
PubMed
Summary
This summary is machine-generated.

Optimizing magnetic resonance imaging (MRI) acquisition parameters improves brain white matter fiber orientation estimation in crossing fiber areas. This study provides a method using the Cramér-Rao Bound (CRB) for precise tuning.

Keywords:
Cramér–Rao boundMulti-tensor modelMultiple-receiver coilsNon-central Chi distribution

More Related Videos

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
15:48

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Published on: December 15, 2014

23.4K
Diffusion Imaging in the Rat Cervical Spinal Cord
10:46

Diffusion Imaging in the Rat Cervical Spinal Cord

Published on: April 7, 2015

12.3K

Related Experiment Videos

Last Updated: Mar 13, 2026

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
09:33

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases

Published on: July 28, 2013

29.4K
Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
15:48

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

Published on: December 15, 2014

23.4K
Diffusion Imaging in the Rat Cervical Spinal Cord
10:46

Diffusion Imaging in the Rat Cervical Spinal Cord

Published on: April 7, 2015

12.3K

Area of Science:

  • Neuroimaging
  • Diffusion MRI
  • Computational anatomy

Background:

  • Accurate estimation of white matter (WM) fiber orientation is crucial for understanding brain structure and function.
  • Crossing fibers in WM present a significant challenge for traditional diffusion MRI analysis.
  • The Multi-Tensor Model (MTM) offers a more robust approach to modeling complex WM architecture.

Purpose of the Study:

  • To investigate the impact of MR acquisition parameters on estimating WM fiber orientation and clinical parameters within crossing fiber regions using the MTM.
  • To develop and apply a methodology for optimizing these acquisition parameters for improved estimation precision.

Main Methods:

  • Computation of the Cramér-Rao Bound (CRB) for the MTM and key clinical parameters like Fractional Anisotropy (FA).
  • Development of an approximate closed-form formula for the Fisher Information Matrix for multi-coil, multi-shell diffusion MRI acquisitions.
  • Generalization of FA and mean diffusivity concepts to the multi-tensor model.

Main Results:

  • Demonstrated that CRB can guide scan time reduction while maintaining high estimation precision.
  • Showcased how increasing the number of acquisition coils can compensate for fewer diffusion gradient directions.
  • Analyzed the influence of b-value and Signal-to-Noise Ratio (SNR), revealing quadratic error variance reduction with SNR and non-unique optimal b-values.

Conclusions:

  • Emphasized the critical importance of selecting appropriate MR acquisition parameters, particularly for analyzing crossing fiber areas.
  • Presented a CRB-based methodology for the optimal tuning of acquisition parameters to enhance the reliability of diffusion MRI analyses.