Start reworking the example.

RunExample.m

+%% Example de-projection script.
+
+%% clear all.
+
+close all
+clear
+clc
+
+%% Parameters, scripts and files location.
+
+% Add DeProj functions to the path.
+addpath('./src')
+
+% Where are the images.
+root_folder = 'samples';
+
+% You can proovide directly the segmentation results as a mask image, and
+% the code below will convert it into a list of objects.
+% For this to work, the mask image must be an 'ImageJ' mask, that is: the
+% cell contours must be black (pixel value == 0) and the cell interiors
+% must be white (pipxel value > 0).
+mask_filename       = 'Segmentation.tif';
+
+% The height-map is an image that stores at every pixel the location of the
+% plane of interest in the source 3D image. Since the pixel values store 
+% the index of the plane, we will need to convert it to an elevation in µm
+% (see the voxel_depth parameter below).
+heighmap_filename   = 'HeightMap.tif';
+
+% Pixel XY size.
+% Physical size of a pixel in X and Y. This will be used to report sizes in
+% µm.
+pixel_size = 0.183; % µm
+
+% Z spacing.
+% How many µm bewtween each Z-slices. We need this to convert the
+% height-map values, that stores the plane of interest, into µm.
+voxel_depth = 1.; % µm
+
+%% Read a mask file and convert it to objects.
+
+% ImageJ mask.
+fprintf('Opening mask image: %s\n', mask_filename )
+I = imread( fullfile( root_folder, mask_filename ) );
+
+% The conversion can take up to 30s for a 1000 x 1000 mask image.
+fprintf('Converting mask to objects.\n' )
+tic 
+[ objects, junction_graph ] = mask_to_objects( I );
+fprintf('Converted a %d x %d mask in %.1f seconds.\n', size(I,1), size(I,2), toc )
+
+% Plot the segmentation.
+figure
+imshow( ~I , [ 0 2 ], 'Border', 'tight' )
+hold on
+
+plot( junction_graph, ...
+    'XData', junction_graph.Nodes.Centroid(:,1), ...
+    'YData', junction_graph.Nodes.Centroid(:,2), ...
+    'LineWidth', 2, ...
+    'EdgeColor', 'b', ...
+    'EdgeAlpha', 1, ...
+    'Marker', 'o', ...
+    'MarkerSize', 4, ...
+    'NodeColor', 'r' )

src/InputSegmentation.m

-
-
-close all
-clear
-clc
-
-mask_path = 'GT.tif';
-
-% ImageJ mask.
-I = imread( mask_path );
-
-tic 
-[ objects, junction_graph ] = mask_to_objects( I );
-fprintf('Analyzed a %d x %d mask in %.1f seconds.\n', size(I,1), size(I,2), toc )
-
-%% Plot everything.
-
-figure
-imshow( ~I , [ 0 2 ], 'Border', 'tight' )
-hold on
-
-plot( junction_graph, ...
-    'XData', junction_graph.Nodes.Centroid(:,1), ...
-    'YData', junction_graph.Nodes.Centroid(:,2), ...
-    'LineWidth', 2, ...
-    'EdgeColor', 'b', ...
-    'EdgeAlpha', 1, ...
-    'Marker', 'o', ...
-    'MarkerSize', 4, ...
-    'NodeColor', 'r' )