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

You might also read

Related Articles

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

Sort by
Same author

An MRI Atlas of the Human Fetal Brain: Reference and Segmentation Tools for Fetal Brain MRI Analysis.

Scientific data·2026
Same author

Comparison of dynamic contrast-enhanced MRI versus MAG-3 scintigraphy for differential renal function assessment in pediatric patients.

Pediatric radiology·2026
Same author

Ultrasonography of pediatric cutaneous and subcutaneous masses.

Pediatric radiology·2026
Same author

Ultrasonography of benign pediatric fibrous and adipocytic lumps.

Pediatric radiology·2026
Same author

Reply to Editorial Comment on "MR Urography Revealing Renal Physiology: Compensatory Changes in Duplex Kidneys".

Urology·2026
Same author

Comparison of Myeloarchitectonic Feature Recognition of the Primary Visual Cortex at 7 T Relative to 3 T MRI.

Journal of magnetic resonance imaging : JMRI·2026
Same journal

Multi-class segmentation of aortic branches and zones in computed tomography angiography: The AortaSeg24 challenge.

Medical image analysis·2026
Same journal

HiVLR: Hierarchical Vision-Language Reasoning for interpretable zero-shot radiography image understanding.

Medical image analysis·2026
Same journal

FAA-Net: Fetal abdominal anomaly diagnosis in prenatal ultrasound via LLM-enhanced multi-instance learning.

Medical image analysis·2026
Same journal

Wavelet-inspired diffusion model with near-field constraint for real-time echocardiography dehazing.

Medical image analysis·2026
Same journal

Co-assistant networks by pathology foundation model and convolutional neural network for gigapixel whole slide image analysis.

Medical image analysis·2026
Same journal

MBAS2024: A large-scale benchmark for multi-class bi-atrial segmentation in multi-center contrast-enhanced MRIs.

Medical image analysis·2026
See all related articles

Related Experiment Video

Updated: Mar 2, 2026

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
09:30

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease

Published on: December 18, 2016

20.2K

Motion-robust parameter estimation in abdominal diffusion-weighted MRI by simultaneous image registration and model

Sila Kurugol1, Moti Freiman1, Onur Afacan1

  • 1Computational Radiology Laboratory, Department of Radiology, Boston Children's Hospital and Harvard Medical School, Boston, MA, 02115, United States.

Medical Image Analysis
|May 12, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces a motion-compensated diffusion-weighted MRI (DW-MRI) model to improve abdominal imaging accuracy. The new method enhances precision and reduces errors in characterizing tissue microstructure for conditions like Crohn's disease.

Keywords:
AbdomenDiffusion-weighted imagingIntra voxel incoherent motion modelMotion compensation

More Related Videos

Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function
02:09

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

Published on: April 12, 2024

1.1K
Dynamic Contrast Enhanced Magnetic Resonance Imaging of an Orthotopic Pancreatic Cancer Mouse Model
06:24

Dynamic Contrast Enhanced Magnetic Resonance Imaging of an Orthotopic Pancreatic Cancer Mouse Model

Published on: April 18, 2015

15.8K

Related Experiment Videos

Last Updated: Mar 2, 2026

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease
09:30

Quantitative Magnetic Resonance Imaging of Skeletal Muscle Disease

Published on: December 18, 2016

20.2K
Multi-modal Pulmonary Imaging: Using Complementary Information from CT and Hyperpolarized 129Xe MRI to Evaluate Lung Structure-Function
02:09

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

Published on: April 12, 2024

1.1K
Dynamic Contrast Enhanced Magnetic Resonance Imaging of an Orthotopic Pancreatic Cancer Mouse Model
06:24

Dynamic Contrast Enhanced Magnetic Resonance Imaging of an Orthotopic Pancreatic Cancer Mouse Model

Published on: April 18, 2015

15.8K

Area of Science:

  • Medical Imaging
  • Biophysics
  • Quantitative MRI

Background:

  • Quantitative body Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) is vital for detecting abdominal abnormalities and monitoring treatment response in conditions like cancer and inflammatory bowel disease.
  • Current DW-MRI models often neglect physiological motion (respiratory, cardiac, peristaltic), potentially compromising the accuracy and robustness of parameter estimations.
  • Accurate parameter estimation is crucial for reliable diagnosis and therapeutic monitoring in abdominal diseases.

Purpose of the Study:

  • To introduce a novel DW-MRI signal decay model that explicitly accounts for motion, aiming to improve parameter estimation accuracy and robustness.
  • To evaluate the performance of the proposed motion-compensated model against conventional methods using in-vivo human datasets.

Main Methods:

  • Developed a Simultaneous Image Registration and Model Estimation (SIR-ME) approach to estimate motion-compensated DW-MRI parameters.
  • The SIR-ME model leverages the interdependence of acquired volumes along the diffusion-weighting dimension to solve image registration and model estimation concurrently.
  • Applied the SIR-ME model to in-vivo DW-MRI datasets from Crohn's disease patients and liver imaging studies.

Main Results:

  • In Crohn's disease patients, SIR-ME reduced the coefficient of variation for diffusion parameters (D, D*, f) by up to 24% and decreased classification error rates for normal/abnormal bowel loops by up to 13% compared to independent registration.
  • In liver imaging, SIR-ME improved parameter estimation precision, reducing the coefficient of variation by up to 23% compared to independent registration.
  • The proposed model demonstrated enhanced accuracy and robustness in characterizing tissue microstructure across different abdominal organs.

Conclusions:

  • The SIR-ME model significantly improves the precision and accuracy of quantitative body DW-MRI parameter estimation by effectively compensating for motion.
  • This advancement holds promise for more reliable detection and monitoring of abdominal pathologies, including inflammatory bowel disease and cancer.
  • The SIR-ME approach represents a valuable tool for enhancing the clinical utility of quantitative body DW-MRI in characterizing tissue microstructure.