Segmentation of Polyp Instruments using UNet based deep learning model
DOI:
https://doi.org/10.5617/nmi.9145Keywords:
Artificial Intelligence, Machine Learning, DeepLearning, Biomedical Image SegmentationAbstract
In this paper, we present a UNet architecture-based deep learning method that is used to segment polyp and instruments from the image data set provided in the MedAI Challenge2021. For the polyp segmentation task, we developed a UNet based algorithm for segmenting polyps in images taken from endoscopies. The main focus of this task is to achieve high segmentation metrics on the supplied test dataset. Similarly for the polyp segmentation task, in the instrument segmentation task, we have developed UNet based algorithms for segmenting instruments present in colonoscopy videos.
Downloads
Published
2021-11-01 — Updated on 2021-12-01
Versions
- 2021-12-01 (2)
- 2021-11-01 (1)
Issue
Section
NMI Challenge
License
Copyright (c) 2021 Nordic Machine Intelligence
![Creative Commons License](http://i.creativecommons.org/l/by/4.0/88x31.png)
This work is licensed under a Creative Commons Attribution 4.0 International License.