Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

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

A longitudinally-consistent deep framework for joint subcortical segmentation and registration of infant brains.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society·2026

Same author

TumorSynth: Integrated Brain Tumor and Tissue Segmentation on Brain MRI Scans of Any Resolution and Contrast.

Radiology. Imaging cancer·2026

Same author

Multi-task Joint Prediction of Infant Cortical Morphological and Cognitive Development.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2025

Same author

Prediction of Infant Cognitive Development with Cortical Surface-Based Multimodal Learning.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2025

Same author

Incomplete Multi-Modal Disentanglement Learning With Application to Alzheimer's Disease Diagnosis.

IEEE transactions on medical imaging·2025

Same author

STF: A spherical transformer for versatile cortical surfaces applications.

NeuroImage·2025

Same journal

LiftReg: Limited Angle 2D/3D Deformable Registration.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026

Same journal

Inverse Consistency by Construction for Multistep Deep Registration.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026

Same journal

Can Crowdsourced Annotations Improve AI-based Congestion Scoring For Bedside Lung Ultrasound?

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026

Same journal

Equivariant Filters for Efficient Tracking in 3D Imaging.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026

Same journal

Lobar Lung Density Embeddings with a Transformer encoder (LobTe) to predict emphysema progression in COPD.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026

Same journal

uniGradICON: A Foundation Model for Medical Image Registration.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Aug 30, 2025

How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index

How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index

Published on: January 2, 2012

Learning 4D Infant Cortical Surface Atlas with Unsupervised Spherical Networks.

Fenqiang Zhao¹, Zhengwang Wu¹, Li Wang¹

¹Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention

|September 2, 2022

Summary

This summary is machine-generated.

This study introduces a novel framework for creating a continuous, 4D infant cortical surface atlas using unsupervised learning and longitudinal data. This approach overcomes limitations of existing methods, improving accuracy in analyzing early brain development.

Keywords:

Infant cortical surface atlas Surface registration

More Related Videos

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

Published on: May 20, 2016

Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies

Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies

Published on: December 15, 2023

Related Experiment Videos

Last Updated: Aug 30, 2025

How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index

How to Measure Cortical Folding from MR Images: a Step-by-Step Tutorial to Compute Local Gyrification Index

Published on: January 2, 2012

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery

Published on: May 20, 2016

Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies

Author Spotlight: Bridging Gaps in Anatomy and Establishing a Foundation for Algorithmic Studies

Published on: December 15, 2023

Area of Science:

Neuroimaging
Developmental Neuroscience
Medical Image Analysis

Background:

Spatiotemporal (4D) cortical surface atlases are crucial for understanding infant brain development.
Conventional methods struggle with longitudinal data, leading to discrete, inconsistent, and time-consuming atlas construction.

Purpose of the Study:

To develop a fast, unsupervised learning-based framework for constructing a continuous 4D infant cortical surface atlas.
To incorporate longitudinal constraints for improved temporal correspondence in the atlas space.

Main Methods:

Proposed a novel unsupervised learning framework with longitudinal constraints.
Utilized a multi-level multimodal spherical registration network for coarse-to-fine cortical surface registration.
Constructed a 4D atlas from 625 longitudinal scans of 291 infants.

Main Results:

The developed atlas is temporally continuous, unlike discrete state-of-the-art atlases.
Demonstrated improved intra- and inter-subject spatial normalization accuracy.
Showcased more detailed and fine-grained cortical patterns, enhancing registration accuracy.

Conclusions:

The proposed framework successfully generates a continuous 4D infant cortical surface atlas.
This method offers superior accuracy and efficiency compared to conventional approaches.
The atlas provides a valuable tool for analyzing dynamic early brain development.