Explainable U-Net model forMedical Image Segmentation
03 medical and health sciences
0302 clinical medicine
DOI:
10.5617/nmi.9142
Publication Date:
2021-11-02T11:18:32Z
AUTHORS (2)
ABSTRACT
In this nutshell, we propose a simple, efficient, and explainable deep learning-based U-Net algorithm for the MedAI challenge, focusing on precise segmentation of polyp and instrument and transparency on algorithms. We develop a straightforward encoder-decoder-based algorithm for the task above. We make an effort to make a simple network as much as possible. Specially, we focus on input resolution and width of the model to find the best optimal settings for the network. We perform ablation studies to cover this aspect.
SUPPLEMENTAL MATERIAL
Coming soon ....
REFERENCES (0)
CITATIONS (4)
EXTERNAL LINKS
PlumX Metrics
RECOMMENDATIONS
FAIR ASSESSMENT
Coming soon ....
JUPYTER LAB
Coming soon ....