Poster: A Distributed Deep Reinforcement Learning System for Medical Image Segmentation

被引:0
|
作者
Xu, Lanyu [1 ]
机构
[1] Oakland Univ, Rochester, MI 48063 USA
关键词
Medical image segmentation; deep reinforcement learning; distributed machine learning;
D O I
10.1145/3580252.3589997
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Multi-institutional collaboration is an emerging deployment of medical imaging processing with the goal to address the scarce annotation problem. While most of the efforts in this domain focus on the supervised machine learning models and the model performance improvement, there lack the discussion about the distributed system performance, such as the trade-off between collaboration and efficiency, i.e., communication cost and processing time. In this work, we propose a distributed system based on deep reinforcement learning for medical image segmentation. Preliminary experiments are conducted on single and multiple CPU and GPU environments to demonstrate the system performance and the trade-off. We highlight some insights for better designs of multi-institutional collaboration in the future.
引用
收藏
页码:189 / 191
页数:3
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