Light-weight hybrid convolutional network for liver tumor segmentation

Jianpeng Zhang, Yutong Xie, Pingping Zhang, Hao Chen, Yong Xia, Chunhua Shen

科研成果: 书/报告/会议事项章节会议稿件同行评审

102 引用 (Scopus)

摘要

Automated segmentation of liver tumors in contrast-enhanced abdominal computed tomography (CT) scans is essential in assisting medical professionals to evaluate tumor development and make fast therapeutic schedule. Although deep convolutional neural networks (DCNNs) have contributed many breakthroughs in image segmentation, this task remains challenging, since 2D DCNNs are incapable of exploring the inter-slice information and 3D DCNNs are too complex to be trained with the available small dataset. In this paper, we propose the light-weight hybrid convolutional network (LW-HCN) to segment the liver and its tumors in CT volumes. Instead of combining a 2D and a 3D networks for coarse-to-fine segmentation, LW-HCN has a encoder-decoder structure, in which 2D convolutions used at the bottom of the encoder decreases the complexity and 3D convolutions used in other layers explore both spatial and temporal information. To further reduce the complexity, we design the depthwise and spatiotemporal separate (DSTS) factorization for 3D convolutions, which not only reduces parameters dramatically but also improves the performance. We evaluated the proposed LW-HCN model against several recent methods on the LiTS and 3D-IRCADb datasets and achieved, respectively, the Dice per case of 73.0% and 94.1% for tumor segmentation, setting a new state of the art.

源语言英语
主期刊名Proceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019
编辑Sarit Kraus
出版商International Joint Conferences on Artificial Intelligence
4271-4277
页数7
ISBN(电子版)9780999241141
DOI
出版状态已出版 - 2019
活动28th International Joint Conference on Artificial Intelligence, IJCAI 2019 - Macao, 中国
期限: 10 8月 201916 8月 2019

出版系列

姓名IJCAI International Joint Conference on Artificial Intelligence
2019-August
ISSN(印刷版)1045-0823

会议

会议28th International Joint Conference on Artificial Intelligence, IJCAI 2019
国家/地区中国
Macao
时期10/08/1916/08/19

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