@inproceedings{9b57c8fb1bec48a89483bd7d55d03016,
title = "PnP-AE: A Plug-and-Play Module for Volumetric Medical Image Segmentation",
abstract = "In recent years, 3D volumetric medical images have been widely used in clinical diagnosis, however, the popular 2D networks were reported unsuitable for segmenting them. In this direction, we propose a plug-and-play (PnP-AE) module to improve the performance of using 2D network for 3D medical image segmentation. Our method takes advantage of the intrinsic correlation between adjacent slices, by multiple encoders and fusion components to decouple plane feature extraction and depth information integration. In addition, the proposed weight sharing and feature storage strategies make PnP-AE extremely efficient. Our method is able to conveniently incorporate with mainstream 2D networks to segment 3D volumetric medical images. Experimental results demonstrate the excellent performance of our method. The source code is available at https://github.com/qklee-lz/PnP-AE.",
keywords = "Adjacent information exploration, Feature fusion, Medical image segmentation, Plug-and-play",
author = "Qiankun Li and Xiaolong Huang and Bo Fang and Yani Zhang and Yongyong Chen and Junxin Chen",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023 ; Conference date: 05-12-2023 Through 08-12-2023",
year = "2023",
doi = "10.1109/BIBM58861.2023.10385472",
language = "英语",
series = "Proceedings - 2023 2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2059--2064",
editor = "Xingpeng Jiang and Haiying Wang and Reda Alhajj and Xiaohua Hu and Felix Engel and Mufti Mahmud and Nadia Pisanti and Xuefeng Cui and Hong Song",
booktitle = "Proceedings - 2023 2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023",
address = "美国",
}