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

Imaging Studies IV: Magnetic Resonance Imaging01:27

Imaging Studies IV: Magnetic Resonance Imaging

215
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,...
215
Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

8.9K
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...
8.9K
Brain Imaging01:14

Brain Imaging

640
Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
640

You might also read

Related Articles

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

Sort by
Same author

Respiratory Motion Management in Abdominal MRI: Revisiting the Gap Between Technical Advances and Clinical Translation.

Magnetic resonance in medicine·2026
Same author

L-TGVN: Leveraging Longitudinal Priors for Personalized Rapid MRI.

ArXiv·2026
Same author

Hybrid learning: a combination of self-supervised and supervised learning for joint MRI reconstruction and denoising in low-field MRI.

Physics in medicine and biology·2026
Same author

Software-defined Radar for MRI Motion Correction: A versatile, vendor-independent Platform.

medRxiv : the preprint server for health sciences·2026
Same author

Cardiac-Gated Diffusion-Weighted Magnetic Resonance Imaging Assessment of Kidney Function in Patients With Kidney Cancer.

Kidney international reports·2026
Same author

Seeing my way.

Current problems in diagnostic radiology·2026
Same journal

Structural MRI Volumetry Index for Differentiation of Progressive Supranuclear Palsy From Parkinson's Disease and Multiple System Atrophy by Automatic Segmentation: A Comparison With Magnetic Resonance Parkinsonism Index.

Journal of magnetic resonance imaging : JMRI·2026
Same journal

Integrating nnU-Net Segmentation and Clinical-Radiomics for Multicenter MRI-Based Assessment of Soft Tissue Sarcoma Grade and Ki-67 Expression.

Journal of magnetic resonance imaging : JMRI·2026
Same journal

Optimization of Respiratory Training Methods for Cardiac Magnetic Resonance Imaging.

Journal of magnetic resonance imaging : JMRI·2026
Same journal

Editorial for "Voxel-Wise Radiomics Habitat Analysis of Post-Treatment Gliomas for Noninvasive Differentiation of True Progression and Pseudoprogression".

Journal of magnetic resonance imaging : JMRI·2026
Same journal

Multiparametric Quantitative MRI of Peripheral Nerves to Differentiate Demyelinating From Axonal Polyneuropathies.

Journal of magnetic resonance imaging : JMRI·2026
Same journal

Mapping Fatty Acid Composition in the Human Knee: Short-Term Repeatability at 3T.

Journal of magnetic resonance imaging : JMRI·2026
See all related articles

Related Experiment Video

Updated: Jan 9, 2026

A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
06:08

A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound

Published on: March 21, 2025

1.1K

Artificial Intelligence in Prostate MRI: Addressing Current Limitations Through Emerging Technologies.

Patricia M Johnson1,2,3, Lavanya Umapathy1,2, Bradley Gigax4

  • 1Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University Grossman School of Medicine, New York, New York, USA.

Journal of Magnetic Resonance Imaging : JMRI
|December 5, 2025
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) can enhance prostate MRI for earlier prostate cancer detection and management. AI solutions are improving image acquisition, quality, and interpretation, making prostate MRI more reliable and scalable.

Keywords:
artificial intelligencedeep learningprostate MRI

More Related Videos

Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy
09:11

Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy

Published on: April 9, 2019

22.2K
Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence
08:05

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence

Published on: June 10, 2025

1.1K

Related Experiment Videos

Last Updated: Jan 9, 2026

A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
06:08

A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound

Published on: March 21, 2025

1.1K
Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy
09:11

Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy

Published on: April 9, 2019

22.2K
Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence
08:05

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence

Published on: June 10, 2025

1.1K

Area of Science:

  • Radiology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Prostate MRI is crucial for prostate cancer detection and risk stratification.
  • Current limitations include high costs, interpretation variability, and scalability issues.
  • False negatives, false positives, and long acquisition times affect reliability and throughput.

Purpose of the Study:

  • To review the progress and applications of artificial intelligence (AI) in prostate MRI.
  • To synthesize advancements in AI across five key domains: triage, acquisition, quality assurance, diagnosis, and prognosis.
  • To highlight the evidence level, validation status, and adoption barriers of AI in prostate MRI.

Main Methods:

  • Literature review synthesizing progress in AI for prostate MRI.
  • Analysis of AI applications in patient triage, accelerated acquisition/reconstruction, quality assurance, lesion detection, and prognostic modeling.
  • Evaluation of evidence levels, validation, and barriers to clinical adoption.

Main Results:

  • AI demonstrates significant potential in refining patient triage and accelerating MRI acquisition via deep learning reconstruction.
  • AI models for lesion detection and cancer prediction show performance comparable to radiologists.
  • While acquisition and reconstruction tools are advanced (FDA-cleared), triage, quality control, and prognosis applications are in earlier development stages.

Conclusions:

  • AI offers solutions to improve the reliability, scalability, and efficiency of prostate MRI.
  • Further research and prospective trials are needed to ensure equitable performance and integrate AI into routine clinical practice.
  • AI has the potential to transform prostate MRI into a scalable platform for population-level prostate cancer management.