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

Methadone treatment in the rural and urban United States: Geographic barriers and regional variations in Medicare-enrolled opioid treatment program availability.

Journal of substance use and addiction treatment·2026
Same author

Improving Access to Traumatic Brain Injury Care Through Learning Health Systems Change: Community-Based Participatory Research Through Human-Centered Design.

The Journal of head trauma rehabilitation·2026
Same author

Techno-Economic Comparison Based on Experimental Setup of Spherical and Flat Photovoltaics with IoT Monitoring System.

Sensors (Basel, Switzerland)·2026
Same author

Correction: Omentopexy after laparoscopic sleeve gastrectomy in children and adolescents: is it effective in reducing post-operative complications?

Updates in surgery·2026
Same author

Using Implementation Science to Improve Health Care Access and Quality for People With Traumatic Brain Injury-Related Morbidity (I-HEAL): Protocol for a Translational Multiproject Program Award.

JMIR research protocols·2026
Same author

Omentopexy after laparoscopic sleeve gastrectomy in children and adolescents: is it effective in reducing post-operative complications?

Updates in surgery·2026

Related Experiment Video

Updated: Jul 15, 2026

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration
05:05

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration

Published on: November 23, 2019

Patella sex determination by 3D statistical shape models and nonlinear classifiers.

Mohamed Mahfouz1, Ahmed Badawi, Brandon Merkl

  • 1Biomedical Engineering Department, University of Tennessee, 301 Perkins Hall, Knoxville, TN 37996, United States. mmahfouz@utk.edu

Forensic Science International
|May 8, 2007
PubMed
Summary

Forensic anthropologists can now determine sex from kneecaps using computed tomography (CT) scans and automated feature analysis. This novel method achieves high accuracy, aiding in personal identification from skeletal remains.

More Related Videos

Automated Joint Space Detection Improves Bone Segmentation Accuracy
06:45

Automated Joint Space Detection Improves Bone Segmentation Accuracy

Published on: November 28, 2025

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb
08:24

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb

Published on: August 30, 2016

Related Experiment Videos

Last Updated: Jul 15, 2026

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration
05:05

Four-Dimensional CT Analysis Using Sequential 3D-3D Registration

Published on: November 23, 2019

Automated Joint Space Detection Improves Bone Segmentation Accuracy
06:45

Automated Joint Space Detection Improves Bone Segmentation Accuracy

Published on: November 28, 2025

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb
08:24

Sit-to-stand-and-walk from 120% Knee Height: A Novel Approach to Assess Dynamic Postural Control Independent of Lead-limb

Published on: August 30, 2016

Area of Science:

  • Forensic anthropology
  • Biometrics
  • Medical imaging analysis

Background:

  • Sex determination from skeletal remains is crucial for personal identification.
  • The patella (kneecap) is an underutilized bone for sex estimation.
  • Existing methods for skeletal sex estimation have limitations.

Purpose of the Study:

  • To develop a novel, automated method for sex determination using patellar morphology.
  • To investigate the efficacy of computed tomography (CT) and advanced feature extraction for patellar analysis.
  • To compare the performance of various statistical and neural network classifiers for sex classification from patellar data.

Main Methods:

  • A dataset of 228 patellae was analyzed using high-resolution computed tomography (CT).
  • Automated feature extraction techniques were applied to segmented CT data, including geometric features and principal components.
  • Feature vectors were classified using statistical methods (Linear Discriminant Classification) and neural networks (Feed-forward backpropagation).

Main Results:

  • Automated feature extraction and surface smoothing effectively distinguished patellar variations.
  • Classification rates varied, with Linear Discriminant Classification achieving 90.3% and neural networks reaching 96.02% (training) and 93.51% (testing).
  • The developed method shows significant promise for sex determination from patellae.

Conclusions:

  • This study presents a highly accurate, automated method for sex determination from patellar morphology using CT scans.
  • The application of novel features and nonlinear classifiers (neural networks) offers a valuable tool for forensic anthropology.
  • This technique can aid in the identification of individuals from incomplete skeletal remains.