Multi-frame Abnormality Detection in Video Capsule Endoscopy
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-89880-9_13
Reference22 articles.
1. Adewole, S.: Deep learning methods for anatomical landmark detection in video capsule endoscopy images. pp. 426–434, October 2020
2. Aoki, T., et al.: Automatic detection of erosions and ulcerations in wireless capsule endoscopy images based on a deep convolutional neural network. Gastroint. Endosc. 89(2), 357-363.e2 (2019)
3. Bianco, S., Ciocca, G., Napoletano, P., Schettini, R.: An interactive tool for manual, semi-automatic and automatic video annotation. Comput. Vis. Image Underst. 131, 88–99 (2015)
4. Costa, D.: Clinical performance of new software to automatically detect angioectasias in small bowel capsule endoscopy. GE - Port. J. Gastroenterol. 28, 1–10 (2020)
5. Ding, Z., et al.: Gastroenterologist-level identification of small-bowel diseases and normal variants by capsule endoscopy using a deep-learning model. Gastroenterology 157(4), 1044-1054.e5 (2019)
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