Trainable Weka Segmentation: a machine learning tool for microscopy pixel classification
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Summary
The Trainable Weka Segmentation (TWS), a machine learning tool that leverages a limited number of manual annotations in order to train a classifier and segment the remaining data automatically, is introduced.
- Type
- article
- Published
- 2017-08-01
- Cited by
- 2,111
- References
- 8
- Access
- Open access
- OpenAlex
- https://openalex.org/W2601810315
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:3726330
Keywords
Computer science, Segmentation, Artificial intelligence, Pipeline (software), Bottleneck
References
- Interactive exemplar-based segmentation toolkit for biomedical image analysis
- Improved structure, function and compatibility for CellProfiler: modular high-throughput image analysis software
- The WEKA data mining software: an update
- Ilastik: Interactive learning and segmentation toolkit
- Fiji - an Open Source platform for biological image analysis
- Collaborative analysis of multi-gigapixel imaging data using Cytomine
- Focus on Bio-Image Informatics.
- KNIME for Open-Source BioImage Analysis - A Tutorial
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