Hip Joint Segmentation From Magnetic Resonance Imaging to Generate 3‐Dimensional Models to Assess Femoroacetabular Impingement Syndrome

Accurate assessment of anatomic structures is essential for surgical planning. This is especially relevant for hip arthroscopy for femoroacetabular impingement syndrome. Beyond standard radiographs, 3-dimensional (3D) imaging often is required for preoperative assessment. Although computed tomography provides quick results with exceptional visualization of bone, magnetic resonance imaging (MRI) eliminates the exposure of ionizing radiation and provides superior soft-tissue visualization. This study demonstrates a reproducible process to generate high-quality 3D hip models from MRI using 3D Slicer to advance femoroacetabular impingement syndrome research and clinical decision-making. A 3-T MRI of the hip without contrast was imported into 3D Slicer, specifically focusing on T1 Vibe sequences. The Digital Imaging and Communications in Medicine file was deidentified. Segmentation began by isolating the femur and pelvis along the axial, coronal, and sagittal planes. A preliminary "coarse" segmentation was generated using the "Grow from Seeds" function, which is an automated region growth based on manual inputs. For precise segmentation, boundaries of the segmentation were refined. Once segmentation was complete, an initial 3D model was generated, which was then smoothed.

Authors

Institutions

Publication Details

Journal
Arthroscopy Techniques
Published
2025-07-16
DOI
https://doi.org/10.1016/j.eats.2025.103714
Primary Topic
Hip disorders and treatments
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Hip Joint Segmentation From Magnetic Resonance Imaging to Generate 3‐Dimensional Models to Assess Femoroacetabular Impingement Syndrome

Catherine Yuh, Steven P. Mell, Jesus E Cervantes, Shane Nho
Arthroscopy Techniques
Hip disorders and treatments
article

Hip Joint Segmentation From Magnetic Resonance Imaging to Generate 3‐Dimensional Models to Assess Femoroacetabular Impingement Syndrome

Catherine Yuh, Steven P. Mell, Jesus E Cervantes, Shane Nho
article en

Abstract

Accurate assessment of anatomic structures is essential for surgical planning. This is especially relevant for hip arthroscopy for femoroacetabular impingement syndrome. Beyond standard radiographs, 3-dimensional (3D) imaging often is required for preoperative assessment. Although computed tomography provides quick results with exceptional visualization of bone, magnetic resonance imaging (MRI) eliminates the exposure of ionizing radiation and provides superior soft-tissue visualization. This study demonstrates a reproducible process to generate high-quality 3D hip models from MRI using 3D Slicer to advance femoroacetabular impingement syndrome research and clinical decision-making. A 3-T MRI of the hip without contrast was imported into 3D Slicer, specifically focusing on T1 Vibe sequences. The Digital Imaging and Communications in Medicine file was deidentified. Segmentation began by isolating the femur and pelvis along the axial, coronal, and sagittal planes. A preliminary "coarse" segmentation was generated using the "Grow from Seeds" function, which is an automated region growth based on manual inputs. For precise segmentation, boundaries of the segmentation were refined. Once segmentation was complete, an initial 3D model was generated, which was then smoothed.

Arthroscopy TechniquesVol. 14(8)
Rush University Medical Center (US)
Gender equality
Openalex Percentile: Top 70%
Hip disorders and treatments
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.