Back to Search Start Over

Artificial intelligence for automated detection of congenital brain anomalies in the first trimester:the Rotterdam Periconception Cohort

Authors :
Zijta, M.
Bastiaansen, W.
Steegers, E.
Wijnen, R. M.
Steegers-Theunissen, R. P.
Klein, S.
de Bakker, B. S.
Rousian, M.
Zijta, M.
Bastiaansen, W.
Steegers, E.
Wijnen, R. M.
Steegers-Theunissen, R. P.
Klein, S.
de Bakker, B. S.
Rousian, M.
Source :
Zijta , M , Bastiaansen , W , Steegers , E , Wijnen , R M , Steegers-Theunissen , R P , Klein , S , de Bakker , B S & Rousian , M 2024 , ' Artificial intelligence for automated detection of congenital brain anomalies in the first trimester : the Rotterdam Periconception Cohort ' , Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology , vol. 64 , no. S1 , OC07.06 , pp. 19 .
Publication Year :
2024

Abstract

Here, we showed the first steps towards automatic detection of brain anomalies in first trimester pregnancies using 3D ultrasound images. The next step is to evaluate if the abnormal features correspond with the brain anomalies. In the future, we will extend this algorithm towards a broader age range and towards all anatomical structures to enable automated congenital anomaly screening during the first trimester.

Details

Database :
OAIster
Journal :
Zijta , M , Bastiaansen , W , Steegers , E , Wijnen , R M , Steegers-Theunissen , R P , Klein , S , de Bakker , B S & Rousian , M 2024 , ' Artificial intelligence for automated detection of congenital brain anomalies in the first trimester : the Rotterdam Periconception Cohort ' , Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology , vol. 64 , no. S1 , OC07.06 , pp. 19 .
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1481684079
Document Type :
Electronic Resource