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fit2DGauss.m
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fit2DGauss.m
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function [Fit, ROI, zfit, fiterr, zerr, resnorm, rr] = fit2DGauss(Image,ROI,init,varargin)
% fit2DGauss Fit 2D Gaussian to intrinsic imaging data. Utilizes FMGAUSSFIT
% (https://www.mathworks.com/matlabcentral/fileexchange/41938-fit-2d-gaussian-with-optimization-toolbox)
% FIT = fit2DGauss() prompts the user to select one or more tif files,
% and then fits 2D Gaussians to the loaded images. The initial guess at
% the Gaussian's centroid is the brightest pixel. FIT is a Nx7 vector
% specifying: [Amplitude AxisAngle Sigma_X Sigma_Y Mu_X Mu_Y ?] for each
% Gaussian fit.
%
% fit2DGauss(IMAGE), IMAGE can be an emptry matrix to prompt the user for
% file selection, a cell array of strings of filenames to load, or an
% HxWxN matrix to fit N 2D Gaussians to.
%
% [FIT, ROI] = fit2DGauss(IMAGE,ROI) restricts the 2D Gaussian fit to the
% data within the polygon specified by ROI, a Px2 matrix of the
% perimeter's points. Set ROI to true to prompt for user selection of the
% polygon. Leave ROI as an empty matrix to not use an ROI. To specify
% different ROI parameters for each image, ROI can be a cell array of
% length equal to the number of images input.
%
% fit2DGauss(IMAGE,ROI,INIT) specifies the initial [X,Y] guess of the
% Gaussian's centroid to be INIT. Set INIT to true to prompt for user
% selection of the centroid's initial guess. Leave INIT empty to use the
% default initial guess: the image's brightest pixel. To specify
% different INIT parameters for each image, INIT can be a cell array of
% length equal to the number of images input.
%
% fit2DGauss(...,'Filter',FILTER) applies the 2D filter to the image(s)
% (created by fspecial) prior to fitting. (default =
% fspecial('gaussian',5,1))
%
% fit2DGauss(...,'Invert') toggles inverting the image prior to fitting.
% (default = false)
%
% fit2DGauss(...,'Verbose') toggles displaying the result of the fit
% using overlayGauss. (default = true)
%
% [Fit, zfit, fiterr, zerr, resnorm, rr] = fit2DGauss(...) returns all
% outputs of FMGAUSSFIT. (doesn't work for multiple files currently)
%
% Default parameters that can be adjusted
Filter = fspecial('gaussian',5,1); % false or filtering object created with fspecial
invert = false; % booleon specifying whether to invert image
verbose = true; % booleon specifying whether to display fit
% Placeholders
directory = cd; % default directory when prompting user to select a file
%% Parse input arguments
index = 1;
while index<=length(varargin)
try
switch varargin{index}
case {'Filter','filter'}
Filter = varargin{index+1};
index = index + 2;
case {'Invert','invert'}
invert = ~invert;
index = index + 1;
case {'Verbose','verbose'}
verbose = ~verbose;
index = index + 1;
otherwise
warning('Argument ''%s'' not recognized',varargin{index});
index = index + 1;
end
catch
warning('Argument %d not recognized',index);
index = index + 1;
end
end
if ~exist('Image','var') || isempty(Image)
[Image,p] = uigetfile({'*.tif'},'Choose iOS image',directory,'MultiSelect','on');
if isnumeric(Image)
return
end
Image = fullfile(p,Image);
end
if ischar(Image)
Image = {Image};
end
if ~exist('ROI','var')
ROI = {[]};
elseif ~iscell(ROI)
ROI = {ROI};
end
if ~exist('init','var')
init = {[]};
elseif ~iscell(init)
init = {init};
end
%% Load and transform image
if iscellstr(Image)
for findex = 1:numel(Image)
Image{findex} = imread(Image{findex});
end
Image = cat(3,Image{:});
end
[H,W,numFiles] = size(Image);
if invert
switch class(Image)
case {'single','double'}
Image = realmax(class(Image)) - Image;
otherwise
Image = intmax(class(Image)) - Image;
end
end
if ~isa(Image,'double')
Image = double(Image);
end
if ~isequal(Filter,false)
Image = imfilter(Image,Filter);
end
%% UI
if numel(ROI)==1 && numFiles>1
ROI = repmat(ROI,numFiles,1);
end
if numel(init)==1 && numFiles>1
init = repmat(init,numFiles,1);
end
if any(cellfun(@(x) isequal(x,true), ROI)) || any(cellfun(@(x) isequal(x,true), init))
hF = figure('NumberTitle','off');
for findex = 1:numFiles
% Define ROI
if isequal(ROI{findex},true)
set(hF,'Name',sprintf('%d: Select ROI',findex));
imagesc(Image(:,:,findex)); colormap(gray);
fcn = makeConstrainToRectFcn('impoly',get(gca,'XLim'),get(gca,'YLim'));
h = impoly(gca,'Closed',1,'PositionConstraintFcn',fcn);
pause(2);
ROI{findex} = getPosition(h);
end
% Make guess at centroid
if isequal(init{findex},true)
set(hF,'Name',sprintf('%d: Select centroid',findex));
imagesc(Image(:,:,findex)); colormap(gray);
init{findex} = round(flip(ginput(1)));
end
end
close(hF);
end
%% Fit 2D Gaussian
[xx,yy] = meshgrid(1:H,1:W);
Fit = nan(numFiles,7);
for findex = 1:numFiles
temp = Image(:,:,findex);
if ~isempty(ROI{findex})
mask = poly2mask(ROI{findex}(:,1),ROI{findex}(:,2),H,W);
temp(~mask) = mean(temp(:));
end
[Fit(findex,:), zfit, fiterr, zerr, resnorm, rr] = fmgaussfit(xx,yy,temp,init{findex});
end
%% Display output
if verbose
for findex = 1:numFiles
figure;
imagesc(Image(:,:,findex)); hold on;
overlayGauss(Fit(findex,5:6), Fit(findex,2), Fit(findex,3:4));
if ~isempty(ROI{findex})
plot(ROI{findex}([1:end,1],1),ROI{findex}([1:end,1],2),'r--','LineWidth',2);
end
end
end