Efficient nuclei segmentation based on spectral graph partitioning

Gwo Giun Chris Lee, Shi Yu Hung, Tai Ping Wang, Chun Fu Richard Chen, Chi Kuang Sun, Yi Hua Liao

研究成果: Conference contribution

摘要

Biomedical image processing that offers computer-aided diagnosis is much more popular due to the availability of high quality and large quantity of medical data. Our well-developed biomedical image computing system, which automatically extracts and segments the nucleus and cytoplasm of cell in medical images, is no doubt following this idea. Nonetheless, even though previous system provide good algorithmic performance, its throughput is limited by high computation load and data dependency. Therefore, we deploy spectral graph partitioning to improve computation speed of the most complex module, maker-controlled watershed transform for nuclei detection. By modeling our problem as a graph and embedding architectural costs as the attributes in vertices and edges, we equally distribute workload among processors and reduce overhead in data transfer rate. We deploy the proposed approach on Intel Core i7-930 CPU with four cores and eight threads and test 153 medical images; as a consequence, we achieve less data transfer and better load balance as compared to conventional workload distribution through clustering and other graph partitioning methods.

原文English
主出版物標題ISCAS 2016 - IEEE International Symposium on Circuits and Systems
發行者Institute of Electrical and Electronics Engineers Inc.
頁面2723-2726
頁數4
ISBN(電子)9781479953400
DOIs
出版狀態Published - 2016 七月 29
事件2016 IEEE International Symposium on Circuits and Systems, ISCAS 2016 - Montreal, Canada
持續時間: 2016 五月 222016 五月 25

出版系列

名字Proceedings - IEEE International Symposium on Circuits and Systems
2016-July
ISSN(列印)0271-4310

Other

Other2016 IEEE International Symposium on Circuits and Systems, ISCAS 2016
國家Canada
城市Montreal
期間16-05-2216-05-25

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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