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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