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 Video

Updated: Jul 10, 2026

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells
12:49

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

Published on: September 28, 2019

3D reconstruction of head MRI based on one class support vector machine with immune algorithm.

Lei Wang1, Guizhi Xu, Lei Guo

  • 1Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province in Hebei University of Technology, Tianjin, China, 300130.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|November 16, 2007
PubMed
Summary

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

Research Advances in Pheromone Biosynthesis Regulation via the PBAN Signaling Pathway in Insects.

Insects·2026
Same author

Propagation effects of abnormal beta oscillations on sleep rhythms in Parkinson's disease: A computational study.

Neuroscience·2026
Same author

Corrigendum to "Cross-frequency brain functional network analysis of auditory stimulation in acute disorders of consciousness" [Brain Res. 1870 (2026) 150043].

Brain research·2026
Same author

Spatiotemporal reconfiguration of functional networks by transcranial magnetic stimulation in Alzheimer's disease.

Neuroscience·2026
Same author

[Electric-field modeling, simulation, and experimental analysis of multi-target temporal interference transcranial alternating current stimulation].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi·2026
Same author

Emerging Iced Functional Waters Technologies and Their Applications in Food Preservation.

Comprehensive reviews in food science and food safety·2026

This study explores One Class Support Vector Machine (OCSVM) for accurate 3D MRI reconstruction. Integrating Immune Algorithm and K-fold cross-validation optimizes OCSVM parameters, enhancing reconstruction accuracy.

Area of Science:

  • Medical Imaging
  • Machine Learning
  • Computational Biology

Background:

  • Three-dimensional (3D) reconstruction of MRI images is challenging due to complex and irregular encephalic tissue boundaries.
  • Support Vector Machines (SVM) are widely used for classification and regression tasks based on statistical learning theory.
  • One Class SVM (OCSVM) is a specialized SVM variant designed for specific classification problems.

Purpose of the Study:

  • To explore the application of One Class SVM (OCSVM) for 3D MRI reconstruction.
  • To address the challenge of parameter selection in OCSVM for improved performance.
  • To enhance the accuracy and efficiency of 3D brain tissue reconstruction from MRI data.

Main Methods:

  • Utilized One Class SVM (OCSVM) with kernel functions to identify the smallest hypersphere enclosing target data in high-dimensional space.

Related Experiment Videos

Last Updated: Jul 10, 2026

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells
12:49

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

Published on: September 28, 2019

  • Integrated Immune Algorithm (IA) and K-fold cross-validation for intelligent and optimal parameter searching in OCSVM.
  • Applied the optimized OCSVM approach to 3D MRI image reconstruction.

    • Main Results:

    • Demonstrated the effectiveness of OCSVM in 3D MRI reconstruction.
    • Achieved high reconstruction accuracy using the proposed method.
    • Showcased the benefits of intelligent parameter optimization for OCSVM.

    Conclusions:

    • OCSVM is a viable and effective method for 3D MRI reconstruction.
    • The combination of Immune Algorithm and K-fold cross-validation significantly improves OCSVM parameter selection.
    • The developed approach offers high accuracy for reconstructing complex brain structures from MRI data.