Robust regression of brain maturation from 3D fetal neurosonography using CRNs
We propose a fully three-dimensional Convolutional Regression Network (CRN) for the task of predicting fetal brain maturation from 3D ultrasound (US) data. Anatomical development is modelled as the sonographic patterns visible in the brain at a given gestational age, which are aggregated by the mode...
Κύριοι συγγραφείς: | Namburete, A, Xie, W, Noble, J |
---|---|
Μορφή: | Conference item |
Έκδοση: |
Springer, Cham
2017
|
Παρόμοια τεκμήρια
Παρόμοια τεκμήρια
-
BEAN: brain extraction and alignment network for 3D fetal neurosonography
ανά: Moser, F, κ.ά.
Έκδοση: (2022) -
BEAN: Brain Extraction and Alignment Network for 3D Fetal Neurosonography
ανά: Felipe Moser, κ.ά.
Έκδοση: (2022-09-01) -
VP-Nets : Efficient automatic localization of key brain structures in 3D fetal neurosonography
ανά: Huang, R, κ.ά.
Έκδοση: (2018) -
Registration of 3D fetal neurosonography and MRI.
ανά: Kuklisova-Murgasova, M, κ.ά.
Έκδοση: (2013) -
Plane Localization in 3-D Fetal Neurosonography for Longitudinal Analysis of the Developing Brain
ανά: Yaqub, M, κ.ά.
Έκδοση: (2015)