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1 | 1 | # CellSeg3D: self-supervised (and supervised) 3D cell segmentation, primarily for mesoSPIM data! |
2 | | -[](https://www.napari-hub.org/plugins/napari-cellseg3d) |
| 2 | +[](https://www.napari-hub.org/plugins/napari_cellseg3d) |
3 | 3 | [](https://pypi.org/project/napari-cellseg3d) |
4 | 4 | [](https://pepy.tech/project/napari-cellseg3d) |
5 | 5 | [](https://pepy.tech/project/napari-cellseg3d) |
6 | 6 | [](https://github.com/AdaptiveMotorControlLab/CellSeg3D/raw/main/LICENSE) |
7 | 7 | [](https://codecov.io/gh/AdaptiveMotorControlLab/CellSeg3D) |
8 | 8 | <a href="https://github.com/psf/black"><img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-000000.svg"></a> |
9 | 9 |
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10 | | -<img src="https://images.squarespace-cdn.com/content/v1/57f6d51c9f74566f55ecf271/838605d0-9723-4e43-83cd-6dbfe4adf36b/cellseg-logo.png?format=1500w" title="cellseg3d" alt="cellseg3d logo" width="350" align="right" vspace = "80"/> |
| 10 | +<img src="https://images.squarespace-cdn.com/content/v1/57f6d51c9f74566f55ecf271/838605d0-9723-4e43-83cd-6dbfe4adf36b/cellseg-logo.png?format=1500w" title="cellseg3d" alt="cellseg3d logo" width="150" align="right" vspace = "80"/> |
11 | 11 |
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12 | 12 |
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13 | 13 | **A package for 3D cell segmentation with deep learning, including a napari plugin**: training, inference, and data review. In particular, this project was developed for analysis of confocal and mesoSPIM-acquired (cleared tissue + lightsheet) tissue datasets, but is not limited to this type of data. [Check out our preprint for more information!](https://www.biorxiv.org/content/10.1101/2024.05.17.594691v1) |
@@ -38,7 +38,7 @@ To use the plugin, please run: |
38 | 38 | ``` |
39 | 39 | napari |
40 | 40 | ``` |
41 | | -Then go into `Plugins > napari-cellseg3d`, and choose which tool to use. |
| 41 | +Then go into `Plugins > napari_cellseg3d`, and choose which tool to use. |
42 | 42 |
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43 | 43 | - **Review (label)**: This module allows you to review your labels, from predictions or manual labeling, and correct them if needed. It then saves the status of each file in a csv, for easier monitoring. |
44 | 44 | - **Inference**: This module allows you to use pre-trained segmentation algorithms on volumes to automatically label cells and compute statistics. |
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