Automatic detection of blood content in capsule endoscopy images based on a deep convolutional neural network-Reference-Cited by-同舟云学术

Automatic detection of blood content in capsule endoscopy images based on a deep convolutional neural network

Published:2019-12-27 Issue:7 Volume:35 Page:1196-1200
ISSN:0815-9319
Container-title:Journal of Gastroenterology and Hepatology
language:en
Short-container-title:Journal of Gastroenterology and Hepatology

Author:

Aoki Tomonori¹,Yamada Atsuo¹^ORCID,Kato Yusuke²,Saito Hiroaki³,Tsuboi Akiyoshi⁴,Nakada Ayako¹,Niikura Ryota¹^ORCID,Fujishiro Mitsuhiro⁵,Oka Shiro⁴,Ishihara Soichiro⁶⁷,Matsuda Tomoki³,Nakahori Masato³,Tanaka Shinji⁴,Koike Kazuhiko¹,Tada Tomohiro²⁶⁷

Affiliation:

1. Department of Gastroenterology, Graduate School of MedicineThe University of Tokyo Tokyo Japan

2. AI Medical Service Inc. Tokyo Japan

3. Department of GastroenterologySendai Kousei Hospital Sendai Miyagi Japan

4. Department of EndoscopyHiroshima University Hospital Hiroshima Japan

5. Department of Gastroenterology and HepatologyNagoya University Graduate School of Medicine Nagoya Japan

6. Department of Surgical Oncology, Graduate School of MedicineThe University of Tokyo Tokyo Japan

7. Tada Tomohiro Institute of Gastroenterology and Proctology Saitama Japan

Publisher

Wiley

Subject

Gastroenterology,Hepatology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jgh.14941

Reference12 articles.

1. Wireless capsule endoscopy

2. Wireless capsule endoscopy

3. Suspected blood indicator in capsule endoscopy: a valuable tool for gastrointestinal bleeding diagnosis

4. The validity of suspected blood indicator software in capsule endoscopy: a systematic review and meta-analysis

5. A deep convolutional neural network for bleeding detection in wireless capsule endoscopy images;Xiao J;Conf. Proc. IEEE Eng. Med. Biol. Soc.,2016

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