Polyp and Surgical Instrument Segmentation with Double Encoder-Decoder Networks
<|reference_start|>Polyp and Surgical Instrument Segmentation with Double Encoder-Decoder Networks: This paper describes a solution for the MedAI competition, in which participants were required to segment both polyps and surgical instruments from endoscopic images. Our approach relies on a double encoder-decoder neural network which we have previously applied for polyp segmentation, but with a series of enhancements: a more powerful encoder architecture, an improved optimization procedure, and the post-processing of segmentations based on tempered model ensembling. Experimental results show that our method produces segmentations that show a good agreement with manual delineations provided by medical experts.<|reference_end|>
@article{galdran2024polyp,
    title={Polyp and Surgical Instrument Segmentation with Double Encoder-Decoder
  Networks},
    author={Adrian Galdran},
    journal={NMI, Vol. 1 No. 1 (2021): MedAI: Transparency in Medical Image
  Segmentation},
    year={2024},
    doi={10.5617/nmi.9107},
    archivePrefix={arXiv},
    eprint={2406.03901},
    primaryClass={eess.IV cs.CV cs.LG}
}