bioRxivBioinformaticsPreprint
Convpaint - Universal framework for interactive pixel classification using pretrained neural networks
Lucien HinderlingiD, Guillaume WitziD, Roman SchwobiD, Ana StojiljkovićiD, Maciej DobrzyńskiiD, Mykhailo VladymyroviD, Joël Frei, Benjamin GrädeliD, Agne FrismantieneiD, Olivier C. PertziD
Abstract
We develop Convpaint, a universal computational framework for interactive pixel classification. Convpaint utilizes pretrained convolutional neural networks (CNNs) or vision transformers (ViTs) for feature extraction and enables easy segmentation across a wide variety of tasks. Available within the Python-based napari software ecosystem, Convpaint integrates seamlessly with other plugins into image processing pipelines, which we demonstrate with three workflows across different data modalities.
- assay: imaging
- research focus: clustering
- research focus: dimensionality reduction
- approach: deep learning
- approach: transformer / foundation model
- Citations
- 8
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