Using YOLOv3 to detect colorectal polyps in video

Authors

  • Mary Chris Roperos Go National Institute of Physics, University of the Philippines Diliman
  • Francis N. C. Paraan National Institute of Physics, University of the Philippines Diliman

Abstract

A model based on the You Only Look Once (YOLO) algorithm was trained to detect polyps on a dataset of 503 polyp-positive images taken from colonoscopy video frames. We achieve precision on test sets that is comparable to the performance of a previously described model trained on a much larger set of 5,545 images. However, our model has a lower recall and missed some polyps in the test set.

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Published

2020-10-19

Issue

Section

Complex Systems and Data Analytics (Short Presentations)

How to Cite

[1]
“Using YOLOv3 to detect colorectal polyps in video”, Proc. SPP, vol. 38, no. 1, pp. SPP–2020, Oct. 2020, Accessed: Mar. 25, 2026. [Online]. Available: https://proceedings.spp-online.org/article/view/SPP-2020-2A-05