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# Introduction


A [napari](http://napari.org) plugin for deep-learning based segmentation of cellular structures.

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:alt: schematic of the input & output of Segmenter ML plugin
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- **Available at no cost** --- available on PyPI
- **User-friendly** --- leverage *napari* as a fast 3D viewer with interactive plugin interface
- **Beginner-friendly** --- new to machine learning? This plugin simplifies the application of machine learning in the segmentation process through the 3 main modules:
    - **Curation**: curate training datasets
    - **Training**: iteratively train custom segmentation model(s) (UNET) to target cellular structure with wide morphological variability
    - **Prediction & Thresholding**: generate segmentation prediction on 2D and 3D cell image data

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:alt: screenshot of napari with the Segmenter ML plugin
**Segmenter ML plugin** in *napari* viewer
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## About this User Guide

This document provides an overview of key concepts behind the plugin, offers step-by-step instructions for complete workflows, and share valuable resources, such as available pre-trained models (MegaSeg) and open-access training datasets.



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0_overview
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1_Get-started/0_index_get-started
2_Workflows/0_index_workflows
3_How-do-i/0_index_how-do-i
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:caption: Support
4_Help/0_index_help
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