Convpaint - Universal framework for interactive pixel classification using pretrained neural networks

Hinderling, L.; Witz, G.; Schwob, R.; Stojiljkovic, A.; Dobrzynski, M.; Vladymyrov, M.; Frei, J.; Graedel, B.; Frismantiene, A.; Pertz, O.

doi:10.1101/2024.09.12.610926

bioRxiv · 10.1101/2024.09.12.610926

Convpaint - Universal framework for interactive pixel classification using pretrained neural networks

Hinderling, L.·Witz, G.·Schwob, R.·Stojiljkovic, A.·Dobrzynski, M.·Vladymyrov, M.·Frei, J.·Graedel, B.·Frismantiene, A.·Pertz, O.

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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.

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Hinderling, L., Witz, G., Schwob, R., Stojiljkovic, A., Dobrzynski, M., Vladymyrov, M., Frei, J., Graedel, B., Frismantiene, A., Pertz, O.. 2024-09-14. Convpaint - Universal framework for interactive pixel classification using pretrained neural networks. https://doi.org/10.1101/2024.09.12.610926

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