SynaptophysinROIDil​ation

Synaptophysin Quantification based on Thioflavin Boundary Dilation

% Image Quantification: Border Dilation
% 1. Finds the largest Thioflavin boundary
% 2. Dilates the boundary into small, medium, and large boundaries (users can change in code)
% 3. Computes the fraction of the area of that stains positive for
% synaptophysin within each size boundary
% 4. Computes amount of synaptophysin staining restricted between large and
% medium boundary and medium and small boundary
% synaptophysin stain in dilated boun
% Author: Ricky Savjani, Angie Chiang, Joanna Jankowsky
% Contact: [e-mail]
% Created: 8/2/2017
% Prep:
% 1. Save all images into same folder
% 2. use a distinct flag for thioflavin for each thioflavin image
% (e.g. 'thio' in 'img_2_1_thio.tif')
% 3. use a distinct flag for synaptophysin for each synaptophysin image
% (e.g. 'synapto' in 'img_2_1_synapto.tif')
% Example Usage:
% [outputMat] = SynaptophysinQuantification();
% Input Prompts:
% 1. Input image directory of all image files
% 2. Output directory to save CSV file and all image files
% 3. Thioflavin flag: A Flag to differentiate thioflavin images in the
% input directory
% 4. Synpatophysin flag: A Flag to differentiate thioflavin images in the
% input directory

%Outputs:
% 1.
% % writes the output to a CSV file called 'MaskedVals.csv' with labeled
% headers

% 2.
% Saves all the Synaptophysin Minus Thioflavin B&W Tiff images and the
% thioflavin B&W masks with the boundary dilations