Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Imaging Studies IV: Magnetic Resonance Imaging

Imaging Studies IV: Magnetic Resonance Imaging

Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...

Imaging Studies for Cardiovascular System IV: CMRI

Imaging Studies for Cardiovascular System IV: CMRI

Cardiovascular magnetic resonance imaging, or CMRI, is a non-invasive diagnostic test that employs a magnetic field and radiofrequency waves to create precise images of the heart and arteries. It provides comprehensive information about cardiac anatomy, function, perfusion, and tissue characterization without ionizing radiation.IndicationsCMRI diagnoses various heart conditions, including tissue damage from heart attacks, ischemic heart disease, myocarditis, aortic issues (tears, aneurysms,...

Magnetic Resonance Imaging

Magnetic Resonance Imaging

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...

Imaging Studies I: CT and MRI

Imaging Studies I: CT and MRI

Introduction: MRI and CT scans are crucial advancements in medical imaging techniques, playing a vital role in diagnosing conditions related to the gastrointestinal (GI) system. Each scan serves distinct purposes, targets specific areas, and requires unique nursing duties.
Description of the Procedures
Computed Tomography (CT) scan:
Computed Tomography (CT) scans use X-ray technology to generate detailed images of bones, organs, and tissues. During the scan, the patient lies on a moving table...

You might also read

Related Articles

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

Sort by

Same author

Acute changes in ankle dorsiflexor strength and fNIRS-Derived cortical activation following a single session of neuromuscular electrical stimulation in healthy older adults.

Frontiers in aging·2026

Same author

Machine learning for predicting surgical difficulty of laparoscopic total mesorectal excision for rectal cancer: integrating MR-based pelvimetry and peritoneal reflection.

Frontiers in medicine·2026

Same author

Analysis of cardiac dynamic global function.

JRSM cardiovascular disease·2026

Same author

Deciphering small sequence differences in T cell receptor-antigen pairing.

Nature communications·2026

Same author

A disease-centric vision-language foundation model for precision oncology in kidney cancer.

Nature communications·2026

Same author

MADCrowner: Margin Aware Dental Crown design with template deformation and refinement.

Medical image analysis·2026

Same journal

ContiMorph: An unsupervised learning framework for cardiac motion tracking with time-continuous diffeomorphism.

Medical image analysis·2026

Same journal

MedP-CLIP: Medical CLIP with region-aware prompt integration.

Medical image analysis·2026

Same journal

Multi-organ guided diagnosis of mild cognitive impairment via hierarchical alignment and knowledge distillation.

Medical image analysis·2026

Same journal

SUDA: Simultaneous unsupervised knowledge distillation and adaptation of foundation models for efficient pathological image analysis.

Medical image analysis·2026

Same journal

Beyond the LUMIR challenge: The pathway to foundational registration models.

Medical image analysis·2026

Same journal

Annotation-efficient medical image segmentation via cross-latent graphs and vector-quantized memory.

Medical image analysis·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Nov 21, 2025

Author Spotlight: Optimized Lung MRI Protocol with Computationally Efficient Reconstruction Methods

Author Spotlight: Optimized Lung MRI Protocol with Computationally Efficient Reconstruction Methods

Published on: September 6, 2024

Efficient MR image reconstruction for compressed MR imaging.

Junzhou Huang¹, Shaoting Zhang, Dimitris Metaxas

¹Department of Computer Science, 110 Frelinghuysen Road Piscataway, NJ 08854-8019, USA. jzhuang@cs.rutgers.edu

Medical Image Analysis

|July 12, 2011

Summary

This summary is machine-generated.

This study introduces an efficient algorithm for Magnetic Resonance (MR) image reconstruction, utilizing least squares, total variation (TV), and L1 norm regularization for superior accuracy and speed in compressed sensing scenarios.

More Related Videos

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function

Published on: April 12, 2024

Author Spotlight: Using Hyperpolarized Xenon-129 MRI to Study Lung Diseases

Author Spotlight: Using Hyperpolarized Xenon-129 MRI to Study Lung Diseases

Published on: January 5, 2024

Related Experiment Videos

Last Updated: Nov 21, 2025

Author Spotlight: Optimized Lung MRI Protocol with Computationally Efficient Reconstruction Methods

Author Spotlight: Optimized Lung MRI Protocol with Computationally Efficient Reconstruction Methods

Published on: September 6, 2024

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function

Published on: April 12, 2024

Author Spotlight: Using Hyperpolarized Xenon-129 MRI to Study Lung Diseases

Author Spotlight: Using Hyperpolarized Xenon-129 MRI to Study Lung Diseases

Published on: January 5, 2024

Area of Science:

Medical Imaging
Image Processing
Computational Science

Background:

Magnetic Resonance (MR) imaging is crucial for medical diagnostics.
Compressed sensing enables faster MR image acquisition but requires sophisticated reconstruction algorithms.
Existing reconstruction methods face challenges in balancing accuracy and computational efficiency.

Purpose of the Study:

To develop and evaluate an efficient algorithm for MR image reconstruction.
To improve reconstruction accuracy and reduce computational complexity in compressed MR imaging.
To demonstrate the superiority of the proposed method over existing techniques.

Main Methods:

The proposed algorithm minimizes a combination of least square data fitting, total variation (TV), and L1 norm regularization.
The reconstruction problem is decomposed into L1 and TV norm subproblems.
Subproblems are solved using existing techniques, and solutions are combined iteratively.

Main Results:

The algorithm demonstrates superior performance in terms of reconstruction accuracy compared to previous methods.
Experimental results show reduced computation complexity.
The method is particularly effective for compressed MR image reconstruction.

Conclusions:

The proposed algorithm offers an efficient and accurate solution for MR image reconstruction.
The combined regularization approach (TV and L1) is powerful for compressed MR imaging.
This method advances the field of accelerated medical image acquisition and reconstruction.