Artefact detection and segmentation based on a deep learning system
Gao X., Braden B.
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.