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Use of Variational Autoencoders with Unsupervised Learning to Detect Incorrect Organ Segmentations at CT
PURPOSE: To develop a deep learning model to detect incorrect organ segmentations at CT. MATERIALS AND METHODS: In this retrospective study, a deep learning method was developed using variational autoencoders (VAEs) to identify problematic organ segmentations. First, three different three-dimensiona...
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| I publikationen: | Radiol Artif Intell |
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| Huvudupphovsmän: | , , , , |
| Materialtyp: | Artigo |
| Språk: | Inglês |
| Publicerad: |
Radiological Society of North America
2021
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| Ämnen: | |
| Länkar: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8328105/ https://ncbi.nlm.nih.gov/pubmed/34350410 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1148/ryai.2021200218 |
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