Abstract
One distinct feature of the cerebral cortex is its convex (gyri) and concave (sulci) folding patterns. Due to the remarkable complexity and variability of gyral/sulcal shapes, it has been challenging to quantitatively model their organization patterns. Inspired by the observation that the lines of gyral crests can form a connected graph on each brain hemisphere, we propose a new representation of cortical gyri/sulci organization pattern – gyral net, which models cortical architecture from a graph perspective, starting with nodes and edges obtained from the reconstructed cortical surfaces. A novel computational framework is developed to efficiently and automatically construct gyral nets from surface meshes, and four measurements are devised to quantify the folding patterns. Using an MRI dataset for autism study as a test bed, we identified reduced local connectivity cost and increased curviness of gyral net bilaterally on the parietal lobe, occipital lobe, and temporal lobe in autistic patients. Additionally, we found that the cortical thickness and the gyral straightness of gyral joints are higher than the rest of gyral crest regions. The proposed representation offers a new tool for a comprehensive and reliable characterization of the cortical folding organization. This novel computational framework will enable large-scale analyses of cortical folding patterns in the future.
| Original language | English |
|---|---|
| Pages (from-to) | 14-25 |
| Number of pages | 12 |
| Journal | Medical Image Analysis |
| Volume | 42 |
| DOIs | |
| Publication status | Published - 2017 Dec 1 |
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Keywords
- Autism
- Cortical folding
- Gyral net
- MRI
ASJC Scopus subject areas
- Radiological and Ultrasound Technology
- Radiology Nuclear Medicine and imaging
- Computer Vision and Pattern Recognition
- Health Informatics
- Computer Graphics and Computer-Aided Design
Cite this
Gyral net : A new representation of cortical folding organization. / Chen, Hanbo; Li, Yujie; Ge, Fangfei; Li, Gang; Shen, Dinggang; Liu, Tianming.
In: Medical Image Analysis, Vol. 42, 01.12.2017, p. 14-25.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Gyral net
T2 - A new representation of cortical folding organization
AU - Chen, Hanbo
AU - Li, Yujie
AU - Ge, Fangfei
AU - Li, Gang
AU - Shen, Dinggang
AU - Liu, Tianming
PY - 2017/12/1
Y1 - 2017/12/1
N2 - One distinct feature of the cerebral cortex is its convex (gyri) and concave (sulci) folding patterns. Due to the remarkable complexity and variability of gyral/sulcal shapes, it has been challenging to quantitatively model their organization patterns. Inspired by the observation that the lines of gyral crests can form a connected graph on each brain hemisphere, we propose a new representation of cortical gyri/sulci organization pattern – gyral net, which models cortical architecture from a graph perspective, starting with nodes and edges obtained from the reconstructed cortical surfaces. A novel computational framework is developed to efficiently and automatically construct gyral nets from surface meshes, and four measurements are devised to quantify the folding patterns. Using an MRI dataset for autism study as a test bed, we identified reduced local connectivity cost and increased curviness of gyral net bilaterally on the parietal lobe, occipital lobe, and temporal lobe in autistic patients. Additionally, we found that the cortical thickness and the gyral straightness of gyral joints are higher than the rest of gyral crest regions. The proposed representation offers a new tool for a comprehensive and reliable characterization of the cortical folding organization. This novel computational framework will enable large-scale analyses of cortical folding patterns in the future.
AB - One distinct feature of the cerebral cortex is its convex (gyri) and concave (sulci) folding patterns. Due to the remarkable complexity and variability of gyral/sulcal shapes, it has been challenging to quantitatively model their organization patterns. Inspired by the observation that the lines of gyral crests can form a connected graph on each brain hemisphere, we propose a new representation of cortical gyri/sulci organization pattern – gyral net, which models cortical architecture from a graph perspective, starting with nodes and edges obtained from the reconstructed cortical surfaces. A novel computational framework is developed to efficiently and automatically construct gyral nets from surface meshes, and four measurements are devised to quantify the folding patterns. Using an MRI dataset for autism study as a test bed, we identified reduced local connectivity cost and increased curviness of gyral net bilaterally on the parietal lobe, occipital lobe, and temporal lobe in autistic patients. Additionally, we found that the cortical thickness and the gyral straightness of gyral joints are higher than the rest of gyral crest regions. The proposed representation offers a new tool for a comprehensive and reliable characterization of the cortical folding organization. This novel computational framework will enable large-scale analyses of cortical folding patterns in the future.
KW - Autism
KW - Cortical folding
KW - Gyral net
KW - MRI
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U2 - 10.1016/j.media.2017.07.001
DO - 10.1016/j.media.2017.07.001
M3 - Article
C2 - 28732269
AN - SCOPUS:85024387700
VL - 42
SP - 14
EP - 25
JO - Medical Image Analysis
JF - Medical Image Analysis
SN - 1361-8415
ER -