Does this skill support GPU acceleration?

Yes, the provided logic is designed for Python 3.10+ environments and is optimized for use with CuPy for GPU-accelerated image processing.

How do I handle tiles named by grid position instead of acquisition order?

This skill includes a specific reordering workflow that maps position-indexed tiles (1, 2, 3, 4) back to their physical acquisition order to ensure the stitch model aligns correctly.

Why does standard raster stitching fail for CODEX images?

Standard raster stitching assumes all rows are scanned in the same direction. If applied to a snake pattern, the tiles in every other row will be out of sequence, resulting in a scrambled image.

What is a snake pattern in microscopy?

A snake (or serpentine) pattern alternates scanning direction on each row—moving left-to-right then right-to-left—to minimize microscope stage movement and acquisition time.

Tile Snake Pattern Stitching

Name: Tile Snake Pattern Stitching
Author: smith6jt-cop

bysmith6jt-cop

Data Science & ML

Reconstructs multiplex microscopy images by correctly ordering tiles acquired via snake or serpentine stage patterns.

About

This skill provides standardized logic and Python implementations for stitching microscopy tiles acquired in a snake (boustrophedon) pattern, which is the default for systems like CODEX. It prevents common alignment failures by ensuring that odd-numbered rows are correctly reversed to match physical acquisition order. By providing validated coordinate generation formulas and tile reordering scripts, it allows researchers to accurately reconstruct high-resolution images from raw multiplex data within the KINTSUGI pipeline or similar image processing environments.

Key Features

0 GitHub stars
Integration-ready code for Python 3.10+ and CuPy GPU environments
Support for arbitrary grid sizes including 2x2, 3x3, and larger mosaics
Automated coordinate generation for snake/serpentine tile patterns
Standardized implementation for CODEX and PhenoCycler imaging workflows
Logic for reordering position-named test tiles to match acquisition sequences

Use Cases

Developing high-throughput image processing pipelines for biological research
Stitching CODEX multiplex microscopy image tiles into a single mosaic
Correcting scrambled image reconstructions caused by stage scanning patterns

About

Key Features

0 GitHub stars
Integration-ready code for Python 3.10+ and CuPy GPU environments
Support for arbitrary grid sizes including 2x2, 3x3, and larger mosaics
Automated coordinate generation for snake/serpentine tile patterns
Standardized implementation for CODEX and PhenoCycler imaging workflows
Logic for reordering position-named test tiles to match acquisition sequences

Use Cases

Developing high-throughput image processing pipelines for biological research
Stitching CODEX multiplex microscopy image tiles into a single mosaic
Correcting scrambled image reconstructions caused by stage scanning patterns