Segment Anything for Histopathology

PathoSAM implements interactive annotation and (automatic) instance and semantic segmentation for histopathology images. It is built on top of Segment Anything by Meta AI and our prior work Segment Anything for Microscopy. It specializes Segment Anything for nucleus segmentation in histopathology data. Its core components are:

• The publicly available patho_sam models for interactive data annotation that were fine-tuned on openly available histopathology images.
• The patho_sam library, which provides training functionality based on Segment Anything for Microscopy, and supports:
  • Application of Segment Anything to histopathology images, including whole-slide images, and fine-tuning on your data.
  • Semantic segmentation.

Based on these components, patho_sam enables fast interactive and automatic annotation for histopathology images, see Usage for details.

Installation

How to install patho_sam python library from source:

We recommend to first setup an environment with the necessary requirements:

• environment.yaml: to set up an environment on Linux or Mac OS.
• environment_cpu_win.yaml: to set up an environment on Windows with CPU support.
• environment_gpu_win.yaml: to set up an environment on Windows with GPU support.

To create one of these environments and install patho_sam into it follow these steps:

1. Clone the repository: git clone https://github.com/computational-cell-analytics/patho-sam
2. Enter it: cd patho-sam
3. Create the respective environment: conda env create -f <ENV_FILE>.yaml
4. Activate the environment: conda activate patho-sam
5. Install patho_sam: pip install -e .

Usage

Using example scripts:

See the examples folder for more details.

Using CLI:

• Download the example whole-slide image by running the following via terminal: patho_sam.example_data (see patho_sam.example_data -h for more details about the CLI).

• Run automatic segmentation on your own WSI or the example data by running the following via terminal:

  patho_sam.automatic_segmentation -i /home/anwai/.cache/micro_sam/sample_data/whole-slide-histopathology-example-image.svs -o segmentation.tif

  NOTE 1: See patho_sam.automatic_segmentation -h for more details about the CLI.

  NOTE 2: You can find your cache directory using: python -c "from micro_sam.util import get_cache_directory; print(get_cache_directory())".

Citation

If you are using this repository in your research please cite:

• Our preprint.
• the Segment Anything for Microscopy publication.
• And the original Segment Anything publication.