KINTSUGI Documentation
======================

**Knowledge Integration with New Technologies for Simplified User-Guided Image processing**

Multiplex image processing for challenging datasets with a focus on user integration
rather than automation. This pipeline includes 2D/3D GPU/CPU illumination correction,
stitching, deconvolution, extended depth of focus, registration, autofluorescence
removal, segmentation, clustering, and spatial analysis.

.. image:: CD3e.gif
   :alt: CD3e visualization
   :align: center

Citation
--------

Smith, J. A. et al. Protocol for processing and analyzing multiplexed images
improves lymphatic cell identification and spatial architecture in human tissue.
STAR Protocols 6, 103976 (2025).

Quick Links
-----------

- `Documentation <https://kintsugi.readthedocs.io/>`_
- `GitHub Repository <https://github.com/smith6jt-cop/KINTSUGI>`_
- `Zenodo DOI <https://doi.org/10.5281/zenodo.14984518>`_
- `Test Data <https://zenodo.org/communities/kintsugi>`_

.. toctree::
   :maxdepth: 2
   :caption: Getting Started

   installation
   quickstart

.. toctree::
   :maxdepth: 2
   :caption: User Guide

   workflows
   signal_isolation
   cli
   api

.. toctree::
   :maxdepth: 2
   :caption: Reference

   TROUBLESHOOTING
   DEPENDENCY_ANALYSIS

.. toctree::
   :maxdepth: 1
   :caption: Development

   contributing
   DOCS_MAINTENANCE
   SUBMODULES

.. toctree::
   :maxdepth: 1
   :caption: Technical Notes

   ALGORITHM_OPTIMIZATION_PLAN
   ALGORITHM_OPTIMIZATION_RESULTS
   PERFORMANCE_AUDIT
   evaluation_pyimagej_edf
   kstitch_alternatives_evaluation
   optimization_plan_session
   valis_upstream_bug_report


Indices and tables
==================

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`