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

Search research articles

Related Experiment Video

Updated: Jun 10, 2026

Whole-Brain Single-Cell Imaging and Analysis of Intact Neonatal Mouse Brains Using MRI, Tissue Clearing, and Light-Sheet Microscopy

Whole-Brain Single-Cell Imaging and Analysis of Intact Neonatal Mouse Brains Using MRI, Tissue Clearing, and Light-Sheet Microscopy

Published on: August 1, 2022

CENTS: cortical enhanced neonatal tissue segmentation.

Feng Shi¹, Dinggang Shen, Pew-Thian Yap

¹IDEA Lab, Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599-7515, USA.

Human Brain Mapping

|August 7, 2010

Summary

This summary is machine-generated.

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

Denoising Diffusion-Weighted Images Using Grouped Iterative Hard Thresholding of Multi-Channel Framelets.

Computational diffusion MRI : MICCAI Workshop·2017

Same author

Robust Construction of Diffusion MRI Atlases with Correction for Inter-Subject Fiber Dispersion.

Computational diffusion MRI : MICCAI Workshop·2017

Same author

Robust Fusion of Diffusion MRI Data for Template Construction.

Scientific reports·2017

Same author

Learning-Based Multimodal Image Registration for Prostate Cancer Radiation Therapy.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention·2017

Same author

Segmenting hippocampal subfields from 3T MRI with multi-modality images.

Medical image analysis·2017

Same author

Joint Discriminative and Representative Feature Selection for Alzheimer's Disease Diagnosis.

Machine learning in medical imaging. MLMI (Workshop)·2017

This study introduces a new method for clearer neonatal brain MRI scans, improving brain tissue segmentation accuracy and preserving delicate cortical structures for better analysis.

Area of Science:

Medical Imaging
Neuroscience
Biomedical Engineering

Background:

Neonatal brain MRI acquisition faces challenges due to small head size and low tissue contrast.
These limitations significantly impact subsequent image processing, particularly brain tissue segmentation.

Purpose of the Study:

To enhance the quality of neonatal brain MR images.
To develop an accurate brain tissue segmentation algorithm for fine neonatal brain structures.

Main Methods:

Utilized a dedicated phased array neonatal head coil to improve signal-to-noise ratio and spatial resolution.
Developed a hybrid atlas-based segmentation algorithm incorporating Hessian filtering for cortical gray matter enhancement.
Generated a neonatal population atlas weighted by cortical gray matter similarity.

More Related Videos

Micro-CT Imaging and Morphometric Analysis of Mouse Neonatal Brains

Micro-CT Imaging and Morphometric Analysis of Mouse Neonatal Brains

Published on: May 19, 2023

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Published on: January 7, 2019

Related Experiment Videos

Last Updated: Jun 10, 2026

Whole-Brain Single-Cell Imaging and Analysis of Intact Neonatal Mouse Brains Using MRI, Tissue Clearing, and Light-Sheet Microscopy

Whole-Brain Single-Cell Imaging and Analysis of Intact Neonatal Mouse Brains Using MRI, Tissue Clearing, and Light-Sheet Microscopy

Published on: August 1, 2022

Micro-CT Imaging and Morphometric Analysis of Mouse Neonatal Brains

Micro-CT Imaging and Morphometric Analysis of Mouse Neonatal Brains

Published on: May 19, 2023

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Published on: January 7, 2019

Main Results:

The proposed method achieved superior accuracy in neonatal brain segmentation compared to manual segmentation and other atlas-based methods.
The technique effectively preserved structural details within the cortical regions.
Improved image quality was obtained without increasing data acquisition time.

Conclusions:

The developed hybrid atlas-based segmentation method significantly improves neonatal brain MRI analysis.
The combination of advanced imaging coils and specialized algorithms offers a robust solution for segmenting fine brain structures in neonates.