Creating Mask using variable threshold from an ROI, IR temp data

Good morning,

I apologize for posting this again but my response got flagged as potential spam. The script and image below are what I am working with currently. The script promps the user to select a threshold ROI on the image and calculates the mean and stdev. The user then selects a worm ROI. I need to create a mask that will remove the colder backgrount using the threshold ROI data. I will have to run this script on a large amount of data so the more efficient the better. I am trying to avoid converting to binary and losing the color/temp data. I am new to matlab so any help would be greatly appreciated!

Thank you in advance!!!

image:

Code:

clc;  % Clear command window.
clear;  % Delete all variables.
close all;  % Close all figure windows except those created by imtool.
imtool close all;  % Close all figure windows created by imtool.


load A_Mat_Files/test/12-14-22-IR-000017_1.mat; %Creates 3 files - image is Frame other 2 contain metadata
first_frame = Frame; %First frame - use to set ROIs 

%We will need to always analze left-top agar pad, left bottom, right top,
%right bottom.

%You will need to click on the zoom (looks like a magnifiying glass) to
%zoom in on the image. Do this before you select ROI. After you have zoomed
%click on the magnifying glass again and then select ROI. The ROI should
%look white.

%EDIT's Made - Worm ROI, Threshold ROI, removed range of color map from
%[0:15] or [10:15] to just [] which should auto calculate it, this way the
%ROI has same colors as when selected


%---------Background Left threshold ------------------------------
close all;  % Close all figure windows except those created by imtool.
imshow(first_frame,[],Colormap=jet) ; %can change the diplay range with #'s in []
title('Select ROI for Left threshold background');
hold on 
roi = drawrectangle("Color","w");%draw a rectangular ROI for background
rect_lbg=roi.Position;
%xmin_lbg=round(rect(1)); %records the x-position of the upper left corner as xmin 
%ymin_lbg=round(rect(2)); %records the y-position of the upper left corner as ymin
%width_lbg=round(rect(3)); %records the width of the rectangle as width
%height_lbg=round(rect(4)); %records the length of the rectangle as length
%Store info about the rectangle ROI as we will need them for the frames after frame 1
thres_lbg=imcrop(first_frame,rect_lbg); % crops the image and stores the smaller image in thres_bg
subplot(1,2,1); % plots the cropped and original images side by side so you can make sure they are right
imshow(first_frame,[],Colormap=jet);
title('Original Image')
subplot(1,2,2);
imshow(thres_lbg,[],Colormap=jet);
title('Left Threshold Cropped');


mean_thres_lbg = mean2(thres_lbg); % calculate the mean temp of the background by determining mean of the cropped image
std_thres_lbg= std2(thres_lbg); % calculate the std of the temp of the background by determining std of the cropped image
max_thres_lbg = max(thres_lbg,[],"all"); % calculate the max temp of the background by determining max of the cropped image
min_thres_lbg = min(thres_lbg,[],"all"); % calculate the min temp of the background by determining min of the cropped image

pause; %Allows user to examine cropped and uncropped images to see if the ROI is ok. Hit any key to continue.


%---------------------Worm 1 (left side - worm to the left)----------------

close all;  % Close all figure windows except those created by imtool.
imshow(first_frame,[],Colormap=jet) ; %can change the diplay range with #'s in []
title('Select ROI for Left Worm 1 - leftmost worm');
hold on 
roi = drawrectangle("Color","w");%draw a rectangular ROI for worm 1 using mouse
rect_lw1=roi.Position;
%xmin_lw1=round(rect(1)); %records the x-position of the upper left corner as xmin 
%ymin_lw1=round(rect(2)); %records the y-position of the upper left corner as ymin
%width_lw1=round(rect(3)); %records the width of the rectangle as width
%height_lw1=round(rect(4)); %records the length of the rectangle as length
%Store info about the rectangle ROI as we will need them for the frames after frame 1
Worm_lw1=imcrop(first_frame,rect_lw1); % crops the image and stores the smaller image in Worm_lw1
subplot(1,2,1); % plots the cropped and original images side by side so you can make sure they are right
imshow(first_frame,[],Colormap=jet);
title('Original Image')
subplot(1,2,2);
imshow(Worm_lw1,[],Colormap=jet);
title('Cropped Image for Left Side Worm1 (Leftmost Worm1)');


mean_Worm_lw1 = mean2(Worm_lw1); % calculate the mean temp of the worm by determining mean of the cropped image
std_Worm_lw1 = std2(Worm_lw1); % calculate the std of the temp of the worm by determining std of the cropped image
max_Worm_lw1 = max(Worm_lw1,[],"all"); % calculate the max temp of the worm by determining max of the cropped image
min_Worm_lw1 = min(Worm_lw1,[],"all"); % calculate the min temp of the worm by determining min of the cropped image

pause; %Allows user to examine cropped and uncropped images to see if the ROI is ok. Hit any key to continue.