Small gastric polyp detection based on the improved YOLOv5
Author:
Funder
Science and Technology Innovation Plan Of Shanghai Science and Technology Commission
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11042-024-18497-1.pdf
Reference27 articles.
1. Brosens LA, Wood LD, Offerhaus GJ, Arnold CA, Lam-Himlin D, Giardiello FM, Montgomery EA (2016) Pathology and genetics of syndromic gastric polyps. International journal of surgical pathology 24(3):185–199. https://doi.org/10.1177/1066896915620013
2. Ameling S, Wirth S, Paulus D, Lacey G, Vilarino F (2009) Texture-based polyp detection in colonoscopy. In: Bildverarbeitung Für die Medizin 2009: Algorithmen—Systeme—Anwendungen Proceedings des Workshops Vom 22. Bis 25. März 2009 in Heidelberg, Springer, pp 346–350. https://doi.org/10.1007/978-3-540-93860-6_70
3. Iakovidis DK, Maroulis DE, Karkanis SA, Brokos A (2005) A comparative study of texture features for the discrimination of gastric polyps in endoscopic video. In: 18th IEEE Symposium on computer-based medical systems (CBMS’05), IEEE, pp 575–580. https://doi.org/10.1109/CBMS.2005.6
4. Hwang S, Oh J, Tavanapong W, Wong J, De Groen PC (2007) Polyp detection in colonoscopy video using elliptical shape feature. In: 2007 IEEE International conference on image processing, IEEE, 2:465. https://doi.org/10.1109/ICIP.2007.4379193
5. Bernal J, Sánchez J, Vilarino F (2012) Towards automatic polyp detection with a polyp appearance model. Pattern Recognition 45(9):3166–3182. https://doi.org/10.1016/j.patcog.2012.03.002
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