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Human Fetal Blood Flow Quantification with Magnetic Resonance Imaging and Motion Compensation

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Nesterov accelerated spectral conjugate gradient algorithm for magnetic resonance imaging with TV regularisation.

YueHong Ding¹, ZhiBin Zhu², Shuo Wang³

¹School of Electronic Engineering and Automation. Guangxi Key Laboratory of Automatic Detecting Technology and Instruments, Guilin University of Electronic Technology, Guilin, 541004, China.

Magnetic Resonance Imaging

|December 28, 2025

Summary

This study introduces a new algorithm, TV-NASCG, to improve Magnetic Resonance Imaging (MRI) quality and speed. The Nesterov accelerated spectral conjugate gradient method enhances MRI scans, reducing imaging time and artifacts.

Keywords:

Global convergence Magnetic resonance imaging Nesterov acceleration Powell restart strategy Spectral conjugate gradient method Sufficient descent property

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Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease

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Published on: December 18, 2016

Area of Science:

Medical Imaging
Computational Imaging
Algorithm Optimization

Background:

Magnetic Resonance Imaging (MRI) offers excellent soft tissue resolution without radiation, crucial for diagnosis and drug development.
Current MRI technology faces challenges including long scan times, motion sensitivity, and difficulty balancing image quality with speed.
Optimizing MRI reconstruction algorithms is key to overcoming these limitations.

Purpose of the Study:

To develop an advanced algorithm for Magnetic Resonance Imaging (MRI) reconstruction.
To address limitations of current MRI techniques, specifically scan time and image quality.
To introduce a novel Total Variation (TV) regularized MRI reconstruction algorithm.

Main Methods:

Developed a Nesterov accelerated spectral conjugate gradient algorithm (TV-NASCG) for MRI reconstruction.
Incorporated Total Variation (TV) regularization into the MRI model.
Utilized Nesterov acceleration, step size acceleration, and Powell restart strategies for performance enhancement.
Provided convergence analysis, proving global convergence and sufficient descent properties.

Main Results:

The TV-NASCG algorithm demonstrated improved MRI quality in experimental tests.
The new algorithm significantly shortened MRI imaging time compared to existing methods.
Experimental results validated the effectiveness of TV-NASCG in enhancing MRI performance.

Conclusions:

The TV-NASCG algorithm offers a significant advancement in MRI reconstruction.
This method effectively improves image quality while reducing scan duration.
The proposed algorithm represents a promising solution for overcoming current MRI limitations.