# Segmentation and Reference Point Detection for Laser Capture Microdissection (LMD) ## Project Summary This repository contains the code for a [Cellpose-SAM](https://github.com/MouseLand/cellpose) & [pyLMD](https://github.com/MannLabs/py-lmd) project dedicated to automating **cell boundary and reference point detection** in microscopic images used for **Laser Capture Microdissection (LMD)**. The primary function of this repository is to identify the boundaries of target cells and detect precise reference points from laser engraved 'T' structures and is designed to enhance the reproducibility of the LMD workflow. ## Getting Started ### 📋 Prerequisites This project exclusively uses the [**Pixi**](https://pixi.sh/latest/python/tutorial/) package manager to guarantee a reliable and isolated Python environment. [**Install Instructions**](https://prefix-dev.github.io/pixi/main/install.html) ### 💻 Installation and Setup 1. **Clone the repository:** ```bash git clone https://github.com/Immunodynamics-Engel-Lab/lmd-imageanalysis.git cd lmd-imageanalysis ``` 2. **Initialize the Pixi Environment:** Pixi reads the required dependencies from the `pixi.toml` file and creates a ready-to-use virtual environment. ```bash pixi install ``` ### 📊 FAIR compliance Example data for testing the *in silico* workflow is available on [Zenodo](https://doi.org/10.5281/zenodo.17792441) The workflow is available through [Zenodo](https://doi.org/10.5281/zenodo.20067089) and [WorkflowHub](https://doi.org/10.48546/workflowhub.workflow.2168.1) All resources are publicly accessible and distributed under open licenses where applicable. --- ### ✉️ Correspondence [**Prof. Dr. Daniel R. Engel**](mailto:danielrobert.engel@uk-essen.de): Department of Immunodynamics, Institute of Experimental Immunology and Imaging, University Hospital Essen, Essen, Germany