Automated Segmentation of Epithelial Tissue Using Cycle-Consistent Generative Adversarial Networks
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Summary
This work presents a segmentation method based on cycle consistent generative adversarial networks, which can be trained even in absence of prepared image - mask pairs and shows that it successfully performs image segmentation tasks on samples with substantial defects and even generalizes well to different tissue types.
- Type
- preprint
- Published
- 2018-04-11
- Cited by
- 20
- References
- 26
- Access
- Open access
- OpenAlex
- https://openalex.org/W2799005222
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:5010095
Keywords
Segmentation, Artificial intelligence, Computer science, Pattern recognition (psychology), Convolutional neural network
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- Automated Segmentation of Cardiac Chambers from Cine Cardiac MRI Using an Adversarial Network Architecture
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- ImPartial: Partial Annotations for Cell Instance Segmentation
- Ion Channels in Epithelial Dynamics and Morphogenesis
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- Integrating Artificial Intelligence in Radiotherapy: Challenges and Opportunities in Clinical Workflows
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