Massive Colonoscopy Images Oriented Polyp Detection
Authors: 
Ming Chen, Peng Du, Dong ZhangAuthors Info & Claims
Ming Chen, Peng Du, Dong ZhangAuthors Info & ClaimsPages 95 - 99
Abstract
Since more than 90% of colorectal cancers are converted from colorectal polyps, colonoscopy is the most effective method for early detection of colorectal polyps. However, artificial polyp judgement leads to a high missed diagnosis rate during colonoscopy inspection. To reduce the missed diagnosis rate, we propose an end-to-end deep learning based polyp detection method combining a series of pretreatment methods with a multiple classification based detection network. We have compared our method with several currently popular object detection methods. Experiment results show that our method has effective improvements on detection precision and performance.
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Index Terms
- Massive Colonoscopy Images Oriented Polyp Detection
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Published In
November 2018
156 pages
ISBN:9781450365611
DOI:10.1145/3301879
Copyright © 2018 ACM.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 12 November 2018
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- Research-article
- Research
- Refereed limited
Funding Sources
- Zhejiang Provincial Science and Technology Program in China (No. 2018C01030)
- Public Projects of Zhejiang Province (No. LGF19F020014)
- National Nature Science Foundation of China (No. 61502130, No. 61761136010)
Conference
ICBBE '18
ICBBE '18: 2018 5th International Conference on Biomedical and Bioinformatics Engineering
November 12 - 14, 2018
Okinawa, Japan
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