Artefact detection and segmentation based on a deep learning system
Gao X., Braden B.
Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). This paper presents the results of detection and segmentation of artefact from endoscopic video frames for EAD2020 competition. In this competition, a deep learning based system is applied, which is built upon RetinaNet. Since RetinaNet employs a one-stage method that lacks facilitating masks of segmented objects, inspired by the work of real-time instance segmentation, this system accomplishes object segmentation through two parallel branches to generate a set of prototype masks and to predict per-object mask coefficients respectively. Overall, top 7 (out of 32 entries) position was achieved in this competition on the leaderboard.