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...

You might also read

Related Articles

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

Sort by

Same author

Improved prostate diffusion imaging using deep learning denoising and phase correction with ultra-high-density coil array.

Radiology advances·2026

Same author

VHU-Net: Variational hadamard U-Net for body MRI bias field correction.

Medical image analysis·2026

Same author

Phase II trial protocol of focal prostate ablation combined with androgen deprivation therapy for prostate cancer treatment.

PloS one·2025

Same author

Next-Generation Advances in Prostate Cancer Imaging and Artificial Intelligence Applications.

Journal of imaging·2025

Same author

Post-Treatment Imaging in Focal Therapy: Understanding TARGET and PI-FAB Scoring Systems.

Diagnostics (Basel, Switzerland)·2025

Same author

Surveillance After Focal Therapy for Prostate Cancer: A Comprehensive Review.

Cancers·2025

Search research articles

Related Experiment Video

Updated: May 4, 2026

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly

Published on: April 14, 2014

Computerized liver volumetry on MRI by using 3D geodesic active contour segmentation.

Hieu Trung Huynh¹, Ibrahim Karademir, Aytekin Oto

¹1 Department of Radiology, The University of Chicago, Chicago, IL.

AJR. American Journal of Roentgenology

|December 28, 2013

Summary

An automated 3D liver segmentation scheme accurately measures liver volumes on MRI. This method significantly reduces measurement time compared to manual tracing, achieving excellent agreement with radiologist standards.

More Related Videos

Author Spotlight: A Non-Invasive Tool to Assess and Differentiate Fat Patterns in Liver Using 3D Dixon MRI

Author Spotlight: A Non-Invasive Tool to Assess and Differentiate Fat Patterns in Liver Using 3D Dixon MRI

Published on: October 20, 2023

Author Spotlight: Advancing Hepatic Fibrosis Diagnosis Using Magnetic Resonance Elastography and AI

Author Spotlight: Advancing Hepatic Fibrosis Diagnosis Using Magnetic Resonance Elastography and AI

Published on: July 21, 2023

Related Experiment Videos

Last Updated: May 4, 2026

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly

Lesion Explorer: A Video-guided, Standardized Protocol for Accurate and Reliable MRI-derived Volumetrics in Alzheimer's Disease and Normal Elderly

Published on: April 14, 2014

Author Spotlight: A Non-Invasive Tool to Assess and Differentiate Fat Patterns in Liver Using 3D Dixon MRI

Author Spotlight: A Non-Invasive Tool to Assess and Differentiate Fat Patterns in Liver Using 3D Dixon MRI

Published on: October 20, 2023

Author Spotlight: Advancing Hepatic Fibrosis Diagnosis Using Magnetic Resonance Elastography and AI

Author Spotlight: Advancing Hepatic Fibrosis Diagnosis Using Magnetic Resonance Elastography and AI

Published on: July 21, 2023

Area of Science:

Medical Imaging
Radiology
Computational Anatomy

Background:

Accurate liver volume measurement is crucial in clinical practice.
Manual liver volumetry on MRI is time-consuming and subjective.

Purpose of the Study:

To develop and validate an automated 3D liver segmentation technique for MRI.
To assess the accuracy and efficiency of the automated scheme compared to manual methods.

Main Methods:

A three-stage automated scheme involving preprocessing, fast-marching segmentation, and geodesic active contours.
T1-weighted portal venous phase liver MRI data were used.
Automated volumes were compared against manual tracings by a radiologist.

Main Results:

Excellent agreement between automated and manual liver volumetry (ICC = 0.98).
High accuracy (99.4% ± 0.14%) and Dice overlap (93.6% ± 1.7%).
Automated scheme processing time (1.03 ± 0.13 min) was significantly faster than manual volumetry (24.0 ± 4.4 min).

Conclusions:

The automated 3D liver segmentation scheme provides accurate and reliable liver volume measurements on MRI.
The developed method offers a substantial time-saving advantage over manual volumetry.