Fetal Cortical Plate Segmentation Using Fully Convolutional Networks With Multiple Plane Aggregation

Fetal Cortical Plate Segmentation Using Fully Convolutional Networks With Multiple Plane Aggregation

Fetal magnetic resonance imaging (MRI) has the potential to advance our understanding of human brain development by providing quantitative information of cortical plate (CP) development in vivo. However, for a reliable quantitative analysis of cortical volume and sulcal folding, accurate and automat...

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Bibliographic Details
Main Authors: Jinwoo Hong, Hyuk Jin Yun, Gilsoon Park, Seonggyu Kim, Cynthia T. Laurentys, Leticia C. Siqueira, Tomo Tarui, Caitlin K. Rollins, Cynthia M. Ortinau, P. Ellen Grant, Jong-Min Lee, Kiho Im
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-12-01
Series:Frontiers in Neuroscience
Subjects:
deep learning
fetal brain
cortical plate
segmentation
hybrid loss
MRI
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2020.591683/full

Internet

https://www.frontiersin.org/articles/10.3389/fnins.2020.591683/full

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