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