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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...

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Related Experiment Video

Updated: Jan 17, 2026

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy

Published on: July 2, 2021

Magnetic Resonance Imaging-Based 3-Dimensional Models of the Pelvis and Hip Using Machine Learning for Automatic Bone

Till D Lerch¹, Guodong Zeng², Adam Boschung³

¹Department of Diagnostic, Interventional and Pediatric Radiology, Inselspital, University of Bern, Bern, Switzerland.

Orthopaedic Journal of Sports Medicine

|September 22, 2025

Summary

Automatic segmentation of 3D hip bone models using MRI is as accurate as manual methods for diagnosing femoroacetabular impingement (FAI). This deep learning approach enables efficient, patient-specific surgical planning for hip preservation and arthroscopic procedures.

Keywords:

3D models MRI-based 3D bone models bone segmentation hip arthroscopic surgery hip impingement hip preservation surgery machine learning

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Imaging of the Microstructural Failure Mechanism in the Human Hip

Imaging of the Microstructural Failure Mechanism in the Human Hip

Published on: September 29, 2023

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Last Updated: Jan 17, 2026

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy

Published on: July 2, 2021

Imaging of the Microstructural Failure Mechanism in the Human Hip

Imaging of the Microstructural Failure Mechanism in the Human Hip

Published on: September 29, 2023

Area of Science:

Medical imaging analysis
Orthopedic surgery
Artificial intelligence in medicine

Background:

Femoroacetabular impingement (FAI) can lead to hip pain and osteoarthritis.
3D bone models from dynamic hip simulations aid in patient-specific FAI diagnosis.
Manual segmentation of bone models is time-consuming, necessitating automated methods.

Purpose of the Study:

Compare manual and automatic segmentation of MRI-based 3D hip bone models.
Correlate automated segmentation with impingement-free hip range of motion.
Validate the external accuracy of automatic segmentation.

Main Methods:

Retrospective study of 98 hips (30 FAI patients, 19 asymptomatic).
Acquired 3-T MRI using a rapid 3D T1-weighted VIBE Dixon sequence.
Utilized machine learning (CNN) for automatic segmentation; calculated Dice Similarity Coefficient (DSC) and range of motion differences.

Main Results:

Automatic segmentation showed minimal differences (<1 mm) and high DSC (94.1%-97.5%) compared to manual.
Excellent correlation (r=0.93) for impingement-free flexion.
External validation achieved DSC of 92.2%-94.9%.

Conclusions:

Automatic segmentation of MRI-based 3D bone models is accurate for FAI patients.
Enables radiation-free, patient-specific surgical planning for hip preservation and arthroscopic surgery.
Deep learning segmentation is feasible with routine MRI and short acquisition times.