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Abstract #1028

Multi-path Deformable Convolutional Neural Network with Label Distribution Learning for Fetal Brain Age Prediction

Lufan Liao1, Xin Zhang2, Fenqiang Zhao1, Jingjiao Lou1, Li Wang1, Xiangmin Xu2, He Zhang3, and Gang Li1
1Department of Radiology and BRIC, The University of North Carolina at Chapel Hill, Chapel Hill, CA, United States, 2School of Electronic and Information Engineering, South China University of Technology, GUANGZHOU, China, 3Department of Radiology, Obstetrics and Gynecology Hospital, Fudan University, ShangHai, China

In this study, an end-to-end framework, combining deformable convolution and label distribution learning, is developed for fetal brain age prediction based on MRI. Furthermore, a multi-path architecture is proposed to deal with multi-view MRI scenarios. Experiments on the collected dataset demonstrate that the proposed model achieves promising performance.

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