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

Sutures of the Skull01:22

Sutures of the Skull

10.5K
The human skull is composed of several bones that come together to protect the brain and support the structures of the face. The junctions where these bones meet are called sutures.
Sutures are immobile joints between adjacent bones of the skull. The narrow gap between the bones is filled with dense, fibrous connective tissue that unites the bones. The long sutures located between the skull bones are not straight but instead follow irregular, tightly twisting paths. These twisting lines tightly...
10.5K
Overview of the Skull01:08

Overview of the Skull

8.0K
The cranium (skull) is the skeletal structure of the head that supports the face and protects the brain. It is subdivided into the facial bones and the brain case, or cranial vault. The facial bones underlie the facial structures, form the nasal cavity, enclose the eyeballs, and support the teeth of the upper and lower jaws.
The cranial vault surrounds and protects the brain and houses the middle and inner ear structures. This cavity is bounded superiorly by the rounded top of the skull, which...
8.0K
Two-Dimensional (2D) NMR: Overview01:12

Two-Dimensional (2D) NMR: Overview

1.6K
The 1D NMR spectrum of large and complex molecules like natural products has complicated splitting patterns and overlapping signals, which can be easily interpreted using 2-dimensional (2D) NMR. Unlike 1D NMR, 2D NMR has two frequency axes that provide the coupling information between the nucleus A and nucleus B in a molecule. The process from which 2D spectra are obtained has four steps.
The first step is the preparation period, during which nucleus A is excited with a radiofrequency pulse....
1.6K
2D NMR: Overview of Homonuclear Correlation Techniques01:16

2D NMR: Overview of Homonuclear Correlation Techniques

678
Homonuclear correlation spectroscopy (COSY) is a powerful technique used in Nuclear Magnetic Resonance (NMR) spectroscopy to study the correlations between nuclei of the same type within a molecule. It provides information about scalar couplings between adjacent nuclei, which helps determine connectivity and structural information. There are several COSY variants, each with its unique strengths and experimental parameters.
COSY90 is the standard two-dimensional (2D) COSY experiment that...
678
2D NMR: Overview of Heteronuclear Correlation Techniques01:18

2D NMR: Overview of Heteronuclear Correlation Techniques

813
Heteronuclear correlation spectroscopy is an analytical technique that investigates the coupling between different types of nuclei, often a proton and an X-nucleus, such as carbon-13 or nitrogen-15. This method is commonly used in nuclear magnetic resonance (NMR) spectroscopy to gain insights into complex chemical compounds' structural and compositional aspects. A typical heteronuclear correlation spectrum displays X-nucleus chemical shifts on one axis and a proton spectrum on the other...
813
2D NMR: Homonuclear Correlation Spectroscopy (COSY)01:06

2D NMR: Homonuclear Correlation Spectroscopy (COSY)

2.0K
Homonuclear correlation spectroscopy, or COSY, is a 2-dimensional NMR technique that provides information about coupled protons. Typically, the geminal and vicinal coupling are observed. For example, consider the COSY spectrum of ethyl acetate, where its 1D proton NMR spectrum is plotted along the vertical and horizontal axes with their corresponding chemical shift scale. Three spots on the diagonal corresponding to the three peaks in the 1D proton spectrum are called diagonal peaks. The COSY...
2.0K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Pharyngeal Airway Changes Following Bimaxillary Orthognathic Surgery in Asian Patients.

The Journal of craniofacial surgery·2026
Same author

SurgNavAR: An Augmented Reality Surgical Navigation Framework for Optical See-Through Head Mounted Displays.

IEEE transactions on visualization and computer graphics·2026
Same author

A Prospective, International, Multicentre Registry of Patients Undergoing Segmental Mandibular Defect Reconstruction After Mandibular Resection for Tumours and Drug-Induced Osteonecrosis: A Study Protocol.

Craniomaxillofacial trauma & reconstruction·2026
Same author

Alloplastic total temporomandibular joint (TMJ) replacement registry: a protocol for a prospective global multicentre observational cohort study.

BMJ open·2026
Same author

Genetic and epidemiologic assessment of mandibular cortical indices and bone mineral density in peripubertal children: the Generation R study.

Clinical oral investigations·2025
Same author

Long-term health-related quality of life following segmental mandibulectomy and osseous reconstruction.

Oral oncology·2025

Related Experiment Video

Updated: Feb 11, 2026

Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans
10:23

Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans

Published on: September 8, 2023

3.7K

Automated human skull landmarking with 2D Gabor wavelets.

Markus A de Jong1,2,3, Atilla Gül1, Jan Pieter de Gijt1

  • 1Department of Oral & Maxillofacial Surgery, Special Dental Care, and Orthodontics, Erasmus MC University Medical Center Rotterdam, Rotterdam, Netherlands.

Physics in Medicine and Biology
|April 21, 2018
PubMed
Summary

This study introduces an automated method for identifying anatomical landmarks on skull CT scans. The novel approach achieves 1-2mm accuracy, aiding surgery planning and skull alignment.

More Related Videos

Author Spotlight: Learning Systematic Bronchoscopy in a Simulation-Base Setting
04:47

Author Spotlight: Learning Systematic Bronchoscopy in a Simulation-Base Setting

Published on: June 23, 2023

3.6K
Optical Scatter Microscopy Based on Two-Dimensional Gabor Filters
14:58

Optical Scatter Microscopy Based on Two-Dimensional Gabor Filters

Published on: June 2, 2010

10.0K

Related Experiment Videos

Last Updated: Feb 11, 2026

Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans
10:23

Author Spotlight: Three-Dimensional Cephalometric Landmark Annotation Demonstration on Human Cone Beam Computed Tomography Scans

Published on: September 8, 2023

3.7K
Author Spotlight: Learning Systematic Bronchoscopy in a Simulation-Base Setting
04:47

Author Spotlight: Learning Systematic Bronchoscopy in a Simulation-Base Setting

Published on: June 23, 2023

3.6K
Optical Scatter Microscopy Based on Two-Dimensional Gabor Filters
14:58

Optical Scatter Microscopy Based on Two-Dimensional Gabor Filters

Published on: June 2, 2010

10.0K

Area of Science:

  • Medical Imaging
  • Computer-Aided Surgery
  • Biomedical Engineering

Background:

  • Accurate skull landmarking is crucial for surgical planning, comparative studies, and morphometrics.
  • Current manual landmarking methods can be time-consuming and prone to variability.

Purpose of the Study:

  • To develop and validate an automated method for anatomical landmark detection on cone beam CT (CBCT) skull models.
  • To assess the accuracy and efficiency of the automated method compared to human raters and existing software.

Main Methods:

  • Utilized 2D Gabor wavelets and ensemble learning for automatic landmark localization on CBCT skull surfaces.
  • Validated the algorithm using inter- and intra-rater studies on 39 scans and skull superimposition with Maxilim software.

Main Results:

  • Achieved 1-2mm accuracy for landmarks in the nasal region, comparable to or exceeding human inter-rater variability.
  • Identified accurate landmarks in the eye sockets and lower jaw, suitable for clinical applications.
  • Demonstrated modest training requirements (30-40 scans) and a generic approach for adaptable landmark sets.

Conclusions:

  • The automated landmarking method provides accurate and reliable results for skull CT scans.
  • This technique facilitates automated skull superimposition, enhancing clinical applications in surgery planning and analysis.
  • The method's generic nature and modest training needs support its scalability for larger cohort studies.