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: May 7, 2026

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
11:28

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Published on: June 30, 2018

A Simple and Fast Method of 3D Registration and Statistical Landmark Localization for Sparse Multi-Modal/Time-Series

I Volkau1, F Puspitasari, T T Ng

  • 1Biomedical Imaging Laboratory, Agency for Science Technology and Research; Singapore - igor@sbic.a-star.edu.sg.

The Neuroradiology Journal
|September 14, 2013
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

GAN-MRI enhanced multi-organ MRI segmentation: a deep learning perspective.

Radiological physics and technology·2025
Same author

Harnessing artificial intelligence in radiology to augment population health.

Frontiers in medical technology·2023
Same author

Editorial: New challenges and future perspectives in pathological conditions.

Frontiers in behavioral neuroscience·2023
Same author

Neuroanatomical subtypes of schizophrenia and relationship with illness duration and deficit status.

Schizophrenia research·2022
Same author

Machine learning classification of schizophrenia patients and healthy controls using diverse neuroanatomical markers and Ensemble methods.

Scientific reports·2022
Same author

Correction to: CAFT: a deep learning-based comprehensive abdominal fat analysis tool for large cohort studies.

Magma (New York, N.Y.)·2021

We developed a fast, simple neuroimage registration method for sparse data, enabling multi-modal and time-series analysis. This technique accurately identifies brain landmarks even in low-quality scans.

Area of Science:

  • Medical Imaging
  • Computational Neuroscience
  • Radiology

Background:

  • Traditional neuroimage registration is often slow and requires high-quality scans.
  • Handling sparse or low-quality neuroimaging data presents significant challenges for analysis.

Purpose of the Study:

  • To introduce a simple, fast neuroimage registration method adaptable for sparse data.
  • To enable intra-patient multi-modal and time-series neuroimage registration.
  • To facilitate accurate landmark identification in challenging neuroimaging datasets.

Main Methods:

  • Elliptical approximation of the brain cortical surface near the midsagittal plane (MSP).
  • 3D affine transformation registration based on fitted elliptical parameters and MSP alignment.
  • Statistical localization of landmarks using a dataset of 53 healthy structural scans.

More Related Videos

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
12:09

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy

Published on: August 5, 2014

Related Experiment Videos

Last Updated: May 7, 2026

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging
11:28

Concurrent EEG and Functional MRI Recording and Integration Analysis for Dynamic Cortical Activity Imaging

Published on: June 30, 2018

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
08:45

Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example

Published on: October 24, 2012

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
12:09

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy

Published on: August 5, 2014

Main Results:

  • The method successfully performs multi-modal registration and analyzes stroke time series (hemorrhagic and ischemic).
  • It enables landmark identification, including commissures and superior/inferior brain landmarks, even in sparse or low-visibility neuroimages.
  • Accurate statistical localization of invisible or indiscernible landmarks in sparse morphological and non-morphological images was achieved.

Conclusions:

  • This novel method offers a fast and simple solution for neuroimage registration and landmark identification with sparse data.
  • It demonstrates efficacy across various applications, including multi-modal analysis and longitudinal stroke studies.
  • The technique enhances the analysis of neuroimages where traditional methods may fail due to data quality or sparsity.