A prior knowledge-guided convolutional neural network model for predicting fetal brain age from MRI during second and third trimesters
Fangmei Zhu, Shijie Huang, Xue Tang, Kai zhang, Jian Wang, Dinggang Shen, Zhongxiang Ding · 2025
Read A prior knowledge-guided convolutional neural network model for predicting fetal brain age from MRI during second and third trimesters by Fangmei Zhu, Shijie Huang, Xue Tang, Kai zhang, Jian Wang, Dinggang Shen, Zhongxiang Ding (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-12699803.txt.
Description
Fangmei Zhu and six co-authors gauge how well a neural network guided by prior knowledge can guess unborn baby brain age from MRI scans. Brain age from scans can flag growth that drifts from the norm. The study came out in twenty twenty-five.
Scans came from the second and third thirds of pregnancy, with hundreds of scan sets in three planes. True age came from early pregnancy ultrasound reads. The guided network learned to match that age, scored by match and error gauges. The team also fed the network's focus maps into a brain cutting network, to test if the focus traits truly mark brain zones, and weighed their method against past ones.
Catalog record
| CREATOR | Fangmei Zhu, Shijie Huang, Xue Tang, Kai zhang, Jian Wang, Dinggang Shen, Zhongxiang Ding |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 34 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |