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

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 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,...

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

From Scarcity to Synthesis: Continual Learning Integrates Supervised and Unsupervised CT Image Recovery Models.

IEEE journal of biomedical and health informatics·2026

Same author

MGTP: Multi-Granularity Textual Prompts for Low-Dose Brain PET Image Denoising via Adversarial Diffusion Model.

IEEE journal of biomedical and health informatics·2025

Same author

Adaptive Hardness-Driven Augmentation and Alignment Strategies for Multisource Domain Adaptations.

IEEE transactions on neural networks and learning systems·2025

Same author

Multiple angle key points detection guided screening of unruptured intracranial aneurysms.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025

Same author

Mesh Regression Based Shape Enhancement Operator Designed for Organ Segmentation.

IEEE journal of biomedical and health informatics·2025

Same author

DFCL: Dual-pathway fusion contrastive learning for blind single-image visible watermark removal.

Neural networks : the official journal of the International Neural Network Society·2025

Same journal

Non-invasive classification of stable HFpEF using a deep learning model trained on acoustic features of sustained vowels.

Biomedical engineering online·2026

Same journal

Lung cancer multimodal auxiliary diagnosis based on entropy weight decision fusion.

Biomedical engineering online·2026

Same journal

Potentials of BMSCs for regulating osteogenic-vascular-neural-lymphatic coupling in bone regeneration.

Biomedical engineering online·2026

Same journal

Protein adsorption at material interface: mechanistic design framework for engineering ceramic scaffolds for bone repair applications.

Biomedical engineering online·2026

Same journal

Machine learning models of segmentation in acute ischemic stroke: a systematic review and meta-analysis.

Biomedical engineering online·2026

Same journal

The influence of successful septal myectomy on myocardial stress distributions in the left ventricle: a computational analysis.

Biomedical engineering online·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Mar 21, 2026

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research

Published on: January 5, 2024

Global denoising for 3D MRI.

Xi Wu¹, Zhipeng Yang¹, Jing Peng¹

¹Department of Computer Science, Chengdu University of Information Technology, No.24 Block 1, Xuefu Road, Chengdu, 610225, People's Republic of China.

Biomedical Engineering Online

|May 14, 2016

Summary

This summary is machine-generated.

This study introduces a novel global filtering framework for 3D MRI denoising, significantly improving accuracy and efficiency. The method enhances existing patch-based techniques and works with multimodal MRI datasets.

Keywords:

3D MRI Global denoising Nyström method k-means clustering

More Related Videos

Neuroimaging-Guided TMS–EEG for Real-Time Cortical Network Mapping

Neuroimaging-Guided TMS–EEG for Real-Time Cortical Network Mapping

Published on: June 13, 2025

3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol

3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol

Published on: May 12, 2019

Related Experiment Videos

Last Updated: Mar 21, 2026

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research

Author Spotlight: Methodologies and Advancements of Chronic Pain Management Research

Published on: January 5, 2024

Neuroimaging-Guided TMS–EEG for Real-Time Cortical Network Mapping

Neuroimaging-Guided TMS–EEG for Real-Time Cortical Network Mapping

Published on: June 13, 2025

3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol

3D Scanning Technology Bridging Microcircuits and Macroscale Brain Images in 3D Novel Embedding Overlapping Protocol

Published on: May 12, 2019

Area of Science:

Medical Imaging
Image Processing
Computational Neuroscience

Background:

Denoising is crucial for Magnetic Resonance Imaging (MRI) preprocessing.
Existing patch-based denoising methods struggle with computational efficiency and accuracy, especially for multimodal datasets with varying SNR and resolutions.

Purpose of the Study:

To propose a modified global filtering framework for 3D MRI denoising.
To address the limitations of patch-based methods in terms of computational efficiency and accuracy.

Main Methods:

A modified global filtering framework for 3D MRI is proposed.
A similarity weighting matrix is computed using the entire dataset for each denoising voxel.
K-means clustering and Nyström method are used to approximate the large weighting matrix for computational viability.

Main Results:

The adaptive Nyström low-rank approximation achieved competitive estimation compared to exact global filters.
The sampling rate was reduced by four orders of magnitude.
The global filter improved patch-based methods in both spatial and transform domains.

Conclusions:

A global denoising framework for 3D MRI is presented, utilizing information from the entire dataset.
Nyström low-rank approximation with adaptive k-means clustering significantly reduces sampling rate and running time.
The method is effective for multimodal MRI datasets and enhances existing patch-based techniques.