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

Computed Tomography01:10

Computed Tomography

Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
Magnetic Resonance Imaging01:24

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 III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
Imaging Studies IV: Magnetic Resonance Imaging01:27

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,...

You might also read

Related Articles

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

Sort by
Same author

Characterizing Metabolic and Compositional Heterogeneity of Calf Muscle Using CEST MRI at 3 T.

NMR in biomedicine·2026
Same author

Multi-sampling allows intra-tumoral heterogeneity querying and vulnerability profiling in glioblastoma.

Neuro-oncology·2026
Same author

A potential Adjunctive Role of 7T MRI and Amino-Acid PET in Localizing MRI-Occult Functional Pituitary Microadenomas: A Scoping Review.

AJNR. American journal of neuroradiology·2026
Same author

Clinical Evaluation of Deep Learning-Reconstructed Postcontrast 3D T1-Weighted Volume Interpolated Breath-Hold Examination (VIBE) Compared with Standard VIBE for Detection of Internal Auditory Canal Lesions.

AJNR. American journal of neuroradiology·2026
Same author

Normative T<sub>1</sub> and T<sub>2</sub> Brain Atlases Across the Adult Lifespan in a Chinese Cohort: Multicenter Quantitative MRI Benchmarks for Ageing and Neurodegenerative Research.

Human brain mapping·2026
Same author

Efficient vision mamba for MRI super-resolution via hybrid selective scanning.

Medical physics·2026
Same journal

CT-Guided Epidural Blood Patch for Postoperative Lumbar Cerebrospinal Fluid Leak: A Case Series and Clinical Outcomes.

AJNR. American journal of neuroradiology·2026
Same journal

Clinical Outcomes of Isolated Subarachnoid Hemorrhage after Mechanical Thrombectomy.

AJNR. American journal of neuroradiology·2026
Same journal

Validation of an Automated ASPECTS Software via a Multi-Reader Multi-Case Clinical Reader Study.

AJNR. American journal of neuroradiology·2026
Same journal

Gender Trends in Authorship Across Neuroradiology Journals (2016-2025).

AJNR. American journal of neuroradiology·2026
Same journal

Outcomes of Endovascular Treatment in Large Vessel Occlusions Due to Intracranial Atherosclerotic Disease: A Systematic Review and Updated Meta-Analysis of 11,326 Patients.

AJNR. American journal of neuroradiology·2026
Same journal

Quantitative Impact of T1 Subtraction Maps on Enhancing Component Delineation and Measured Volumes in Minimally Enhancing Pediatric Brain Tumors.

AJNR. American journal of neuroradiology·2026
See all related articles

Related Experiment Video

Updated: May 16, 2026

Cardiac Magnetic Resonance Imaging at 7 Tesla
09:14

Cardiac Magnetic Resonance Imaging at 7 Tesla

Published on: January 6, 2019

Achieving Ultra-High Acceleration Rates in 7T MRI Using Combined Controlled Aliasing in Parallel Imaging and

Erik H Middlebrooks1, Xiangzhi Zhou2, Shengzhen Tao2

  • 1From the Department of Radiology (E.H.M., X.Z., S.T., V.N.P., J.O.E., E.M.W., V.G.), Neurologic Surgery (E.H.M.), Mayo Clinic, Jacksonville, Florida; Swiss Innovation Hub (T.Y., G.F.P.), Siemens Healthineers International AG, Lausanne, Switzerland; Department of Radiology (T.Y.), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland; LTS5, Ecole Polytechnique Fédérale de Lausanne (T.Y.), Lausanne, Switzerland and Research & Clinical Translation (D.N.), Magnetic Resonance, Advanced Systems (J.H., P.L.), Magnetic Resonance, Siemens Healthineers AG, Erlangen, Germany. Middlebrooks.Erik@mayo.edu.

AJNR. American Journal of Neuroradiology
|May 14, 2026
PubMed
Summary
This summary is machine-generated.

Accelerated 7T MRI using combined compressed sensing (CS) and controlled aliasing in parallel imaging (CAIPI) with deep learning (DL) reconstruction significantly reduces scan time. This hybrid approach maintains image quality and lowers motion-related artifacts for rapid, high-resolution brain imaging.

More Related Videos

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla
08:51

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla

Published on: February 19, 2021

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

Related Experiment Videos

Last Updated: May 16, 2026

Cardiac Magnetic Resonance Imaging at 7 Tesla
09:14

Cardiac Magnetic Resonance Imaging at 7 Tesla

Published on: January 6, 2019

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla
08:51

Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla

Published on: February 19, 2021

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

Area of Science:

  • Magnetic Resonance Imaging (MRI)
  • Medical Imaging Physics
  • Artificial Intelligence in Medicine

Background:

  • Clinical adoption of 7 Tesla (7T) MRI is hindered by long acquisition times.
  • Existing acceleration techniques like controlled aliasing in parallel imaging (CAIPI) and compressed sensing (CS) can introduce artifacts and noise.
  • Deep learning (DL) offers potential for artifact reduction in MRI.

Purpose of the Study:

  • To develop and evaluate a unified deep learning framework combining CAIPI and CS for accelerated 7T MRI.
  • To leverage the strengths of CAIPI (improved conditioning) and CS (incoherent undersampling) within a DL reconstruction.
  • To enable higher acceleration factors and reduce scan time while maintaining diagnostic image quality.

Main Methods:

  • A paired within-subject study involving 30 patients for 7T SPACE FLAIR and 30 patients for 7T SPACE T2 acquisitions.
  • Comparison of a reference CAIPI-DL protocol (acceleration factor=6, ~7 min) with a CS-CAIPI-DL protocol (acceleration factor=14, ~3.5 min).
  • Quantitative image quality assessment using metrics like SSIM, SNR, GDME, CNR, noise, ghosting ratio, and NIQE, alongside blinded qualitative evaluations.

Main Results:

  • The CS-CAIPI-DL protocol achieved approximately 50% scan time reduction without significant differences in CNR or noise.
  • Significantly lower ghosting ratios were observed with CS-CAIPI-DL for both FLAIR (~10%) and T2 (~30%) sequences, indicating reduced motion artifacts.
  • Improved NIQE scores for T2 and a favorable trend for FLAIR were noted, with no significant difference in diagnostic adequacy or DL-specific artifacts.

Conclusions:

  • Combining CS, CAIPI, and DL reconstruction enables over twofold acceleration in 7T MRI without compromising key image quality metrics.
  • Shorter scan times were associated with significantly reduced ghosting, supporting the reduction of motion-related artifacts.
  • This hybrid approach demonstrates the feasibility of rapid, high-resolution 7T brain MRI acquisition.