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 Experiment Videos

Border-tracing algorithm implementation for the femoral geometry reconstruction.

D Testi1, C Zannoni, A Cappello

  • 1Laboratorio di Tecnologia Medica, Istituti Ortopedici Rizzoli, Via di Barbiano 1/10, 40136 Bologna, Italy. testi@tecno.ior.it

Computer Methods and Programs in Biomedicine
|May 8, 2001
PubMed
Summary
This summary is machine-generated.

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

Multi-platform satellite-derived products during the 2025 Etna eruption.

Scientific data·2025
Same author

A multiscale orchestrated computational framework to reveal emergent phenomena in neuroblastoma.

Computer methods and programs in biomedicine·2023
Same author

Involvement of transcribed lncRNA uc.291 and SWI/SNF complex in cutaneous squamous cell carcinoma.

Discover oncology·2022
Same author

Delivering computationally-intensive digital patient applications to the clinic: An exemplar solution to predict femoral bone strength from CT data.

Computer methods and programs in biomedicine·2021
Same author

Evaluation of patient tissue selection methods for deriving equivalent density calibration for femoral bone quantitative CT analyses.

Bone·2020
Same author

Effect of size and location of simulated lytic lesions on the structural properties of human vertebral bodies, a micro-finite element study.

Bone reports·2020
Same journal

Facial iPPG heatmap patterns based on period-aware autoencoder show association with carotid atherosclerosis towards non-contact hemodynamic assessment.

Computer methods and programs in biomedicine·2026
Same journal

Explainable machine learning models predict liver fibrosis risk and outcome in the general population: Development and multi-cohort external validation.

Computer methods and programs in biomedicine·2026
Same journal

Evaluation of surrogate endpoints for survival outcomes using the surrogate package in R.

Computer methods and programs in biomedicine·2026
Same journal

Relative spectral and frication-based descriptors as numerical indicators of place of articulation shifts in fricatives produced by Polish children.

Computer methods and programs in biomedicine·2026
Same journal

Leaflet resection improves valve expansion and hemodynamic performance in redo TAVI with balloon- and self-expanding transcatheter heart valve configurations.

Computer methods and programs in biomedicine·2026
Same journal

Spectral super-resolution for Parkinson's voice via representation-level methods under mixed-reality acquisition.

Computer methods and programs in biomedicine·2026
See all related articles

This study introduces an automatic border-tracing method for extracting bone contours from CT scans, crucial for custom hip prostheses. The new method demonstrated superior accuracy and repeatability compared to manual and threshold-based techniques.

Area of Science:

  • Orthopaedic surgery
  • Biomedical engineering
  • Medical imaging analysis

Background:

  • Accurate reconstruction of bone morphology, particularly the femoral medullary canal, is essential for custom orthopaedic implants like hip prostheses.
  • Existing methods for extracting bone geometry from computed tomography (CT) images vary in accuracy and repeatability.

Purpose of the Study:

  • To implement and validate an automatic border-tracing method for extracting bone contours from CT images.
  • To compare the accuracy and repeatability of the border-tracing method against manual and threshold-based techniques.

Main Methods:

  • A composite human femur replica was scanned using CT.
  • CT images were processed using three methods: manual contour extraction, an automatic border-tracing algorithm, and a threshold-based method.

Related Experiment Videos

  • Accuracy was assessed by comparing extracted contours; repeatability was evaluated using in vivo CT datasets.

    • Main Results:

    • Both automated methods (border-tracing and threshold-based) were more accurate than the manual procedure.
    • The border-tracing method exhibited the highest repeatability in critical regions identified from in vivo CT data.
    • Inter-femur repeatability was evaluated across six in vivo CT datasets.

    Conclusions:

    • The automatic border-tracing method offers a highly accurate and repeatable solution for extracting femoral medullary canal geometry from CT images.
    • This technique holds significant potential for improving the design and fit of custom-made orthopaedic implants.