Dette er en utdatert versjon publisert 2021-11-01. Les den nyeste versjonen.
Kvasir-Instruments and Polyp Segmentation Using UNet
DOI:
https://doi.org/10.5617/nmi.9130Emneord (Nøkkelord):
UNet, segmentation, deep learning, polyp, instrumentationSammendrag
This paper aims to describe the methodology used to develop, fine-tune and analyze a UNet model for creating masks for two datasets: Polyp Segmentation and Instrument Segmentation, which are part of MedAI challenge. For training and validation, we have used same methodology on both tasks and finally on
the hidden testing dataset the model resulted with accuracy of 0.9721, dice score of 0.7980 for the instrumentation task, and the accuracy of 0.5646 and a dice score of 0.4100 was achieved for the Polyp Segmentation.
Nedlastinger
Publisert
2021-11-01
Versjoner
- 2021-12-09 (2)
- 2021-11-01 (1)
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NMI Challenge