2022
DOI: 10.12688/f1000research.110283.1
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Automated segmentation of endometriosis using transfer learning technique

Abstract: Background: This paper focuses on segmenting the exact location of endometriosis using the state-of-art technique known as U-Net. Endometriosis is a progressive disorder that has a significant impact on women. The lesion-like appearance that grows inside the uterus and sheds for every periodical cycle is known as endometriosis. If the lesion exists and is transferred to other locations in the women’s reproductive system, it may lead to a serious problem. Besides radiologists deep learning techniques exist for … Show more

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Cited by 1 publication
(2 citation statements)
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“…Source code available from: https://github.com/visalaxi/Automated-segmentation-of-Endometriosis-using-Transfer-Learning Archived source code at time of publication: https://doi.org/10.5281/zenodo.6324521. 47 License: Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).…”
Section: Data Availabilitymentioning
confidence: 99%
See 1 more Smart Citation
“…Source code available from: https://github.com/visalaxi/Automated-segmentation-of-Endometriosis-using-Transfer-Learning Archived source code at time of publication: https://doi.org/10.5281/zenodo.6324521. 47 License: Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).…”
Section: Data Availabilitymentioning
confidence: 99%
“…lists the various hyper parameters identified for execution. The model is available from GitHub and is archived with Zenodo 47. …”
mentioning
confidence: 99%