🧬 IAM – Image Analysis Macros

Author: Veeramohan Veerapandian
Date: 5 June 2025

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📋 Repository Contents

• macros/
  • merge_channels.ijm – Adjust contrast and merge multi-channel images
  • quantify_nuclei.ijm – Quantify OSX/RUNX2/DAPI/SP7-like nuclear signals
• examples/ – Optional: sample input images (upload .tif files)
• results/ – Example outputs (merged PNGs or TIFFs and quantification CSV in .csv)
• README.md – This documentation file

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1️⃣ Merge Channels Macro (merge_channels.ijm)

Purpose:

• Adjust contrast, clean up images per channel (OSX, EMCN, CD31, DAPI)
• Merge selected channels and add a scale bar
• Save composite outputs

Workflow Highlights:

1. Prompts for input and output directories
2. Imports only files with "Stitching" in the name using Bio‑Formats
3. Rotates, splits, enhances each channel:
   • C1 (OSX) → Grayscale, sharpened
   • C2 (CD31) → Green, despeckled
   • C4 (EMCN) → Red, local contrast enhanced
   • C3 (DAPI) → Blue
4. Generates merged output channels like OSX/EMCN/CD31 and EMCN/CD31 with scale bar
5. Saves PNGs to output folder

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2️⃣ Quantify Nuclei Macro (quantify_nuclei.ijm)

Purpose:

• Quantify nuclear signals (e.g., OSX, RUNX2, DAPI, SP7) from stacked image series

Workflow Highlights:

1. Prompts for input and output directories
2. Iterates over files with "Stitching"
3. Uses Bio‑Formats to import series 0
4. Crops a user-selected ROI and preprocessing:
   • Background subtraction, despeckle, median + unsharp mask
5. Selects the middle 25 slices, performs a maximum-Z projection
6. Saves the projection TIFF
7. Converts to 8-bit, enhances contrast, applies Otsu threshold, then watershed
8. Detects particles, outlines them, saves outlined TIFF
9. Counts objects, calculates normalized counts, and total area per slice
10. Logs metrics (fileName, seriesIndex, count, normC, totalArea) into OSX_Fixed25norm_Results.csv in the output folder

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🧮 Usage Guide

1. Open either macro in Fiji/ImageJ (Plugins → Macros → Run… or Script Editor → Run)
2. Select the input directory (network or shared folder)
3. Select the output directory (local)
4. Let the script process images:
   • merge_channels → PNG images with scale bars
   • quantify_nuclei → TIFFs and a CSV summary

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📄 Example Outputs

(Upload these once you have sample data)

• merge_channels results:

  • OSXgry_EMCNr_CD31grn_filename.png
  • EMCNr_CD31grn_filename.png

• quantify_nuclei results:

  • TIFF projection: _proj25.tif
  • Outlined TIFF: _proj25_outlined.tif
  • CSV summary: OSX_Fixed25norm_Results.csv

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⚙️ Requirements & Setup

• Fiji (ImageJ) with Bio-Formats Macro Extensions plugin installed
• Customize channel selection logic (selectWindow("C1-…"), etc.) and thresholds as needed
• Adjust 'Stitching' filename filter if your naming convention differs
• For quantify_nuclei, modify ROI size and slice-window parameters based on your data

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📝 Tips & Troubleshooting

• Before running in batch, run on one image to validate results
• Adjust rolling, median, and unsharp values to match your image quality
• For quantify_nuclei, examine the overlay to ensure nuclei are correctly detected before saving

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📜 License & Citation

This work is shared for academic and research use only. Please credit the author if used or modified in published work.

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🙋‍♂️ Contact

Veeramohan Veerapandian
Social: www.linkedin.com/in/dr-veeramohan-veerapandian-388b3217 | https://bsky.app/profile/veeramp.bsky.social | https://x.com/VeeramohanV