Skip to main navigation
Skip to search
Skip to main content
WashU Medicine Research Profiles Home
Help & FAQ
Link opens in a new tab
Search content at WashU Medicine Research Profiles
Home
Profiles
Departments, Divisions and Centers
Research output
CENTS: Cortical enhanced neonatal tissue segmentation
Feng Shi
, Dinggang Shen
, Pew Thian Yap
, Yong Fan
, Jie Zhi Cheng
,
Hongyu An
, Lawrence L. Wald
, Guido Gerig
, John H. Gilmore
, Weili Lin
Roy and Diana Vagelos Division of Biology & Biomedical Sciences (DBBS)
Institute of Clinical and Translational Sciences (ICTS)
Siteman Cancer Center
Division of Radiological Sciences
Biomedical Research Lab
DBBS - Neurosciences
Research output
:
Contribution to journal
›
Article
›
peer-review
44
Link opens in a new tab
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'CENTS: Cortical enhanced neonatal tissue segmentation'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Gray Matter Volume
100%
Tissue Segmentation
100%
Neonatal Brain
100%
Neonatal Tissues
100%
Magnetic Resonance Imaging
66%
Confidence Map
66%
Image Processing
33%
Image Quality
33%
Signal-to-noise Ratio
33%
Cortical Regions
33%
Gray Matter
33%
Brain Magnetic Resonance Imaging
33%
Data Acquisition Time
33%
Manual Segmentation
33%
Segmentation Method
33%
Spatial Resolution
33%
Image Analysis
33%
Head Circumference
33%
Small Head
33%
Atlas-based
33%
Tissue Contrast
33%
Volume Coil
33%
Segmentation Algorithm
33%
Structural Details
33%
Phased Array
33%
Multi-atlas Segmentation
33%
Population-weighted
33%
Gray Matter Structure
33%
Segmented Image
33%
Insufficient Tissue
33%
Phased Array Coils
33%
Head Coil
33%
Brain Tissue Segmentation
33%
Sheet-like
33%
Atlas-based Method
33%
Tissue Probability Maps
33%
Hessian Filter
33%
Computer Science
Image Analysis
100%
Acquisition Time
100%
Manual Segmentation
100%
Segmentation Method
100%
Image Quality
100%
Spatial Resolution
100%
Image Processing
100%
segmentation algorithm
100%
Cortical Region
100%
segmented image
100%
Probability Map
100%
Structural Detail
100%
Signal-to-Noise Ratio
100%
Engineering
Phased Array
100%
Image Analysis
50%
Similarities
50%
Signal-to-Noise Ratio
50%
Acquisition Time
50%
Spatial Resolution
50%
Brain Tissue
50%
Image Processing
50%
Segmentation Method
50%
Structural Detail
50%
Medicine and Dentistry
Gray Matter
100%
Image Quality
25%
Brain Tissue
25%
Signal-to-Noise Ratio
25%
Cephalometry
25%
Fine Structure
25%
Neuroscience
Gray Matter
100%
Magnetic Resonance Imaging
75%
Image Processing
25%
Signal-to-Noise Ratio
25%
Biochemistry, Genetics and Molecular Biology
Signal Noise Ratio
100%
Image Quality
100%