Quantification of fluorescence channel area in TIFF images using MATLAB
Project description:
This package provides a set of MATLAB functions for analyzing multi-channel .tif image datasets. It 
supports reading single-plane TIFF images with channel-specific filename suffixes, generating 
histograms for background threshold evaluation, and quantifying the fractional area of a 
fluorescent channel normalized to another channel.

How to install the project:
This code relies only on standard MATLAB functions and should work on any platform capable of 
running MATLAB (tested on Windows 10, MATLAB R2020b). Simply place the code files and your .tif 
images in accessible folders and add the functions to your MATLAB path.

Running the code:
This workflow involves three functions that should be run in sequence:

1. tif_build_single_plane
Reads TIFF images from a specified folder, grouping by sample name prefixes and channel suffixes.
Inputs:
*	current_folder — folder to return to after reading files (usually your working directory)
*	target_folder — folder containing .tif files to read
*	channel_suffixes — cell array of strings defining channel-specific filename suffixes (e.g. 
{'_0-000.tif', '_1-000.tif', '_2-000.tif'})
Outputs:
*	names — unique sample name prefixes extracted from filenames
*	store_images — cell array of images grouped by sample and channel

2. check_background_thresholds (optional)
Generates and displays histograms of pixel intensities across all samples in a given channel. This 
helps determine appropriate background cutoff thresholds.
Inputs:
*	store_images — from tif_build_single_plane
*	channel_of_interest — index of the channel for which to plot intensity histograms
*	bitdepth — image bit depth (e.g., 256 for 8-bit images)

3. channel_area_quant_from_tif
Quantifies the fractional area of a fluorescence channel above a threshold, normalized to the 
fractional area of another channel. Optionally displays image overlays for quality control.
Inputs:
*	names — from tif_build_single_plane
*	store_images — from tif_build_single_plane
*	quant_channel_index — index of the channel to quantify
*	norm_channel_index — index of the normalizing channel
*	quant_channel_cutoff — intensity cutoff for positive signal in quantification channel
*	bitdepth — image bit depth (used for histogram generation) e.g., 256 for 8-bit images
*	dispoption — set to 1 to display image montages per sample, 0 to suppress
Output:
*	quant_table — MATLAB table containing sample names, fractional areas, and area ratios

Example usage:
Please see image_quant_driver.m for an example of how to run the code.

Acknowledgments:
This work was supported by the joint efforts of The Michael J. Fox Foundation for Parkinson’s 
Research (MJFF) and the Aligning Science Across Parkinson’s (ASAP) initiative. MJFF administers 
the grants ASAP-000282 and ASAP-024268 on behalf of ASAP and itself.