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

Recurrent and metastatic osteoclast-like giant cell tumor of the liver revealed by FDG PET/CT.

Clinical nuclear medicine·2012
Same author

Case-control study of single nucleotide polymorphisms of PSCA and MUC1 genes with gastric cancer in a Chinese.

Asian Pacific journal of cancer prevention : APJCP·2012
Same author

Significance of Aspergillus spp. isolation from lower respiratory tract samples for the diagnosis and prognosis of invasive pulmonary aspergillosis in chronic obstructive pulmonary disease.

Chinese medical journal·2012
Same author

Stage-specific gender differences in cognitive and neuropsychiatric manifestations of vascular dementia.

American journal of Alzheimer's disease and other dementias·2012
Same author

Oncolytic virus-mediated tumor radiosensitization in mice through DNA-PKcs-specific shRNA.

Translational cancer research·2012
Same author

A label-free electrochemiluminescence aptasensor for thrombin based on novel assembly strategy of oligonucleotide and luminol functionalized gold nanoparticles.

Biosensors & bioelectronics·2012

Related Experiment Video

Updated: Apr 23, 2026

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
07:13

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

2.0K

Surface-based automatic coarse registration of head scans.

Fang Li1, Zhijian Song1

  • 1Digital Medical Research Center, Fudan University, Shanghai 200032, China Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai, Shanghai 200032, China.

Bio-Medical Materials and Engineering
|September 18, 2014
PubMed
Summary

This study introduces a novel principal axes-based coarse registration algorithm for neurosurgery. It enhances the robustness and efficiency of surface registration by accurately aligning patient and image spaces.

Keywords:
Image-guided neurosurgeryadaptive Gaussian kernelcoarse registrationheuristicsprincipal axes

More Related Videos

Quantitative Assessment Protocol for Facial Soft Tissue Volumetric Changes with Stereophotogrammetry
06:26

Quantitative Assessment Protocol for Facial Soft Tissue Volumetric Changes with Stereophotogrammetry

Published on: December 9, 2025

342
Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

1.7K

Related Experiment Videos

Last Updated: Apr 23, 2026

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
07:13

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

2.0K
Quantitative Assessment Protocol for Facial Soft Tissue Volumetric Changes with Stereophotogrammetry
06:26

Quantitative Assessment Protocol for Facial Soft Tissue Volumetric Changes with Stereophotogrammetry

Published on: December 9, 2025

342
Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
05:49

Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization

Published on: February 23, 2024

1.7K

Area of Science:

  • Neurosurgery
  • Medical Imaging
  • Computer-Aided Surgery

Background:

  • Surface registration is crucial for image-guided neurosurgery, enabling spatial alignment between patient and image data.
  • Robust and efficient surface registration relies on a two-stage approach: coarse registration followed by fine registration.

Purpose of the Study:

  • To propose a novel coarse registration algorithm based on principal axes for improved surface registration in neurosurgery.
  • To address challenges in aligning different scanning data by developing a heuristic method for determining translation centers.

Main Methods:

  • Extraction of principal axes using an approximated surface with an adaptive Gaussian kernel, ensuring applicability across various scanning data.
  • Heuristic determination of translation centers by identifying candidate pairs and selecting the optimal pair based on minimum registration error after tentative local alignments.

Main Results:

  • Demonstrated automatic registration of two scans of a head phantom.
  • Experimental results confirmed the algorithm's robustness and feasibility for clinical neurosurgical applications.

Conclusions:

  • The proposed principal axes-based coarse registration algorithm is robust and effective.
  • This method shows significant potential for improving the efficiency and accuracy of image-guided neurosurgery.