Merge pull request #33 from UniBoDS4H/feat/api/close-line-algo

Feature/api/close-line-algo

api/algorithms/algorithm_AverageSmallestAndLargest.m

@@ -18,33 +18,16 @@
 %   averageSeg (matrix [height, width]):
 %     The average segmentation.
 %
-% THROWS:
-%   TDSFT:algorithms:
-%     if the input is empty.
-%
 % DESCRIPTION:
 %   Get the average segmentation between the smallest and the largest.
 %   Can be passed as input the smallest and the largest segmentation or an array of
 %   segmentations from which the smallest and the largest are obtained.
 %   The average segmentation is obtained by taking the 1-pixel line in the middle of
 %   the area between the two segmentations.
 function averageSeg = algorithm_AverageSmallestAndLargest(varargin)
-    disp('Getting the average segmentation between the smallest and the largest...');
-
     if nargin == 1
         segmentations = varargin{1};
 
-        % Check if the input is empty, if it is the case throw an exception
-        if isempty(segmentations)
-            throw(MException('TDSFT:algorithms', 'Segmentations array empty'));
-        end
-
-        % If there is only one segmentation, return it
-        if length(segmentations) == 1
-            averageSeg = segmentations{1};
-            return;
-        end
-
         try
             smallest = algorithm_Smallest(segmentations);
             largest = algorithm_Largest(segmentations);
@@ -58,7 +41,7 @@
         throw(MException('TDSFT:algorithms', 'Wrong number of parameters'));
     end
 
-    % Overlap the two smallest and the largest segmentations
+    % Overlap the smallest and the largest segmentations
     averageSeg = smallest + largest;
 
     % Fill the holes and get the area between the two segmentations

api/algorithms/algorithm_AverageTargetFromInput.m

@@ -5,7 +5,7 @@
 % PARAMETERS:
 %   segmentations (Cell array: [1, raters], Cells: matrix [height, width]):
 %     array containing the segmentations to fuse.
-%   startSegmentation (int):
+%   target (int):
 %     the index of the segmentation to be used as main segmentation.
 %
 % OUTPUT:
@@ -14,8 +14,6 @@
 %
 % THROWS:
 %   TDSFT:algorithms:
-%     the segmentations array is empty.
-%   TDSFT:algorithms:
 %     the start segmentation index is greater than the number of segmentations.
 %
 % DESCRIPTION:
@@ -24,20 +22,13 @@
 %   with value 1 in the other segmentations. Then it is computed the average pixel:
 %   - if the segmentations are 2, the average pixel is the middle point between the two pixels;
 %   - if the segmentations are more than 2, the average pixel is the centroid of the pixels. 
-function averageSeg = algorithm_AverageTargetFromInput(segmentations, startSegmentation)
-    s = strcat("Getting average segmentation targetting the segmentation ", num2str(startSegmentation{1}), "...");
-    disp(s);
-
-    % Check if the input is empty, if it is the case throw an exception
-    if isempty(segmentations)
-        throw(MException('TDSFT:algorithms', 'Segmentations array empty'));
-    end
-
+function averageSeg = algorithm_AverageTargetFromInput(segmentations, target)   
     try
-        if startSegmentation{1} > length(segmentations) || startSegmentation{1} < 1
+        % Check if the target segmentation is in the range.
+        if target > length(segmentations) || target < 1
             throw(MException('TDSFT:algorithms', 'Wrong start segmentation index'));
         end
-        averageSeg = getAverageSegmentation(segmentations, startSegmentation{1});
+        averageSeg = getAverageSegmentation(segmentations, target);
     catch ME
         rethrow(ME);
     end

api/algorithms/algorithm_AverageTargetLargest.m

@@ -8,7 +8,7 @@
 %
 % OUTPUT:
 %   averageSeg (matrix [height, width]):
-%     The average segmentation.       
+%     the average segmentation.       
 %
 % DESCRIPTION:
 %   The average segmentation is computed by averaging the segmentations as follows:
@@ -17,13 +17,6 @@
 %   - if the segmentations are 2, the average pixel is the middle point between the two pixels;
 %   - if the segmentations are more than 2, the average pixel is the centroid of the pixels. 
 function averageSeg = algorithm_AverageTargetLargest(segmentations)
-    disp('Getting average segmentation targetting the largest...');
-
-    % Check if the input is empty, if it is the case throw an exception
-    if isempty(segmentations)
-        throw(MException('TDSFT:algorithms', 'Segmentations array empty'));
-    end
-
     try
         largest = algorithm_Largest(segmentations);
         averageSeg = getAverageSegmentation(segmentations, largest);

api/algorithms/algorithm_AverageTargetSmallest.m

@@ -17,16 +17,9 @@
 %   - if the segmentations are 2, the average pixel is the middle point between the two pixels;
 %   - if the segmentations are more than 2, the average pixel is the centroid of the pixels. 
 function averageSeg = algorithm_AverageTargetSmallest(segmentations)
-    disp('Getting average segmentation targetting the smallest......');
-
-    % Check if the input is empty, if it is the case throw an exception
-    if isempty(segmentations)
-        throw(MException('TDSFT:algorithms', 'Segmentations array empty'));
-    end
-
     try
-        largest = algorithm_Smallest(segmentations);
-        averageSeg = getAverageSegmentation(segmentations, largest);
+        smallest = algorithm_Smallest(segmentations);
+        averageSeg = getAverageSegmentation(segmentations, smallest);
     catch ME
         rethrow(ME);
     end

api/algorithms/algorithm_Largest.m

@@ -3,17 +3,10 @@
 % NAME: TDSFT (version 1.0)
 %
 % PARAMETERS:
-%   The function accepts two different input parameters:
-%     1) segmentations (Cell array: [1, raters], Cells: matrix [height, width]):
-%          array containing the segmentations to fuse.
-%
-%     2) segmentations (Matrix [height, width]):
-%          the segmentations are already overlapped in a matrix.
-%          (The algorithm need NO dense segmentations, so to overlap the segmentations no fill holes is needed).
-%
-% THROWS:
-%   TDSFT:algorithms:
-%     throwed if the input is empty.
+%   segmentations (Cell array: [1, raters], Cells: matrix [height, width] || Matrix [height, width]):
+%     - array: array containing the segmentations to fuse;
+%     - matrix: the segmentations are already overlapped in a matrix.
+%       (The algorithm need NO dense segmentations, so to overlap the segmentations no fill holes is needed)
 %
 % OUTPUT:
 %   largestSegmentation (Matrix [height, width]):
@@ -22,30 +15,13 @@
 % DESCRIPTION:
 %   Fuse all the segmentations together overlapping them and getting the largest possible segmentation.
 %   The largest segmentation is the smallest segmentation possible which contains each input segmentation.
-%   To obtain it the segmentations are overlapped and then is returned the perimeter of the area covered by them.
+%   To obtain it the segmentations are overlapped and then is returned the perimeter of the total area covered by them.
 function largestSegmentation = algorithm_Largest(segmentations) 
-    disp('Getting the largest...');
-
     if iscell(segmentations)
-
-        % Check if the input is empty
-        if isempty(segmentations)
-            throw(MException('TDSFT:algorithms', 'Segmentations array empty'));
-        end
-
-        % If there is only one segmentation, return it
-        if length(segmentations) == 1
-            largestSegmentation = segmentations{1};
-            return;
-        end
-
-        try
-            overlap = overlapSegmentations(segmentations);
-        catch ME
-            rethrow(ME);
-        end
+        overlap = overlapSegmentations(segmentations);
     else 
         overlap = segmentations;
     end
-    largestSegmentation = getLargestSegmentation(overlap);
+
+    [~, largestSegmentation] = getLargestArea(overlap);
 end

api/algorithms/algorithm_Middle.m

@@ -14,8 +14,6 @@
 %
 % THROWS:
 %   TDSFT:algorithms:
-%     throwed if the input is empty.
-%   TDSFT:algorithms:
 %     throwed if the number of segmentations is even and the algorithm is not specified.
 %   TDSFT:algorithms:
 %     throwed if the algorithm choosed if the number of segmentations is even is not available.
@@ -29,81 +27,56 @@
 %   Discard outliers until the middle segmentation is reached. To do that iterate over the segmentations and
 %   discard the largest and the smallest segmentation at each iteration.
 %   If the number of segmentations is even specify a method for the last two segmentations left.
+%   The available methods are:
+%     - 'LargestSegmentation': use the largest segmentation.
+%     - 'SmallestSegmentation': use the smallest segmentation.
+%     - 'AverageSmallestAndLargest': use the average between the smallest and the largest segmentation.
 function middleSegmentation = algorithm_Middle(segmentations, algorithm)     
-    disp('Getting the middle...');
-
-    % check if the input is empty
-    if isempty(segmentations)
-        throw(MException('TDSFT:algorithms', 'Segmentations array empty'));
-    end
-
-    % check if the number of segmentations is even and the algorithm is specified
+    % Check if the number of segmentations is even and the algorithm is specified
     if mod(length(segmentations), 2) == 0 && nargin < 2
         throw(MException('TDSFT:algorithms', 'If the number of segmentations is even, the algorithm must be specified'));
     end
 
-    % if there is only one segmentation, return it
-    if length(segmentations) == 1
-        middleSegmentation = segmentations{1};
-        return;
-    end
-
-    try
-        overlap = overlapSegmentations(segmentations);
-    catch ME
-        rethrow(ME);
-    end
+    overlap = overlapSegmentations(segmentations);
 
     nSeg = length(segmentations); % number of segmentations
     totIt = floor( (nSeg - 1) / 2 ); % total number of iterations
 
-    % preallocate the filled segmentations array
-    filledSegmentations = cell(1, length(segmentations));
-
-    % Get the filled segmentations needed to get the smallest segmentation      
-    for i=1:length(segmentations)
-        filledSegmentations{i} = imfill(segmentations{i}, 'holes');
-    end
-
-    try
-        overlapFilled = overlapSegmentations(filledSegmentations);
-    catch ME
-        rethrow(ME);
-    end
+    % Fill segmentations and overlap.
+    filledSegmentations = getFilledSegmentations(segmentations);
+    overlapFilled = overlapSegmentations(filledSegmentations);
 
     % At each iteration discard the largest and the smallest segmentation
     for i=1:totIt
-        largest = uint8( getLargestSegmentation(overlap) );
-        smallest = uint8( getSmallestSegmentation(overlapFilled, nSeg) );
+        largest = uint8( algorithm_Largest(overlap) );
+        smallest = uint8( algorithm_Smallest(overlapFilled, nSeg) );
 
         overlap = overlap - largest;
         overlap = overlap - smallest;
 
-        filledLargest = imfill(largest, 'holes');
-        filledSmallest = imfill(smallest, 'holes');
+        filledLargest = imfill(largest, "holes");
+        filledSmallest = imfill(smallest, "holes");
         overlapFilled = overlapFilled - filledLargest;
         overlapFilled = overlapFilled - filledSmallest;
 
         nSeg = nSeg - 2;
     end
 
-    % compute result
+    % If the number of segmentations is even, use the specified algorithm for the last two segmentations left.
     if isequal(nSeg, 2)
-        % if the number of segmentations is even, use the specified algorithm for the last two segmentations left
-        algorithm = fromSpacedToFullName(algorithm);
+        algorithm = fromSpacedToFullNameAlgorithm(algorithm);
         if strcmp(algorithm, 'algorithm_Largest')
-            middleSegmentation = getLargestSegmentation(overlap);
+            middleSegmentation = algorithm_Largest(overlap);
         elseif strcmp(algorithm, 'algorithm_Smallest')
-            middleSegmentation = getSmallestSegmentation(overlapFilled, nSeg);
+            middleSegmentation = algorithm_Smallest(overlapFilled, nSeg);
         elseif strcmp(algorithm, 'algorithm_AverageSmallestAndLargest')
-            smallest = getSmallestSegmentation(overlapFilled, nSeg);
-            largest = getLargestSegmentation(overlap);
+            smallest = algorithm_Smallest(overlapFilled, nSeg);
+            largest = algorithm_Largest(overlap);
             middleSegmentation = algorithm_AverageSmallestAndLargest(smallest, largest);
         else
             throw(MException('TDSFT:algorithms', 'Algorithm not available'));
         end
     else
-        % if the number of segmentations is odd, return the segmentation left
         middleSegmentation = imbinarize(overlap);
     end
 

api/algorithms/algorithm_STAPLE.m

@@ -10,10 +10,6 @@
 %   gtSegmentation (Matrix [height, width]):
 %     the ground truth segmentation computed with STAPLE algorithm.
 %
-% THROWS:
-%   staple:emptyInput (Exception):
-%     throwed if the input is empty.
-%
 % DESCRIPTION:
 %   Use STAPLE algorithm to get the ground truth segmentation.
 %
@@ -23,37 +19,21 @@
 %   an algorithm for the validation of image segmentation." 
 %   Medical Imaging, IEEE Transactions on 23.7 (2004): 903-921.
 function gtSegmentation = algorithm_STAPLE(segmentations)
-    disp('Executing STAPLE...');
-
-    % check if the input is empty
-    if isempty(segmentations)
-        throw(MException('TDSFT:algorithms', 'Segmentations array empty'));
-    end
-
-    % if there is only one segmentation, return it
-    if length(segmentations) == 1
-        gtSegmentation = segmentations{1};
-        return;
-    end
+    % Convert to the right format for STAPLE.
+    % (See STAPLE file for more details)
 
-    % convert to the right format for STAPLE
-    % See STAPLE file for more details
-
-    % get segmentations dimensions
-    [height, width] = size(segmentations{1});
+    % Get segmentations dimensions.
+    imageDims = size(segmentations{1});
     nSeg = length(segmentations);
 
-    % preallocate the array
-    stapleParam = zeros(height*width, nSeg);
+    % Preallocate the array.
+    stapleParam = zeros(imageDims(1) * imageDims(2), nSeg);
     for i=1:length(segmentations)
         seg = segmentations{i};
         stapleParam(:, i) = seg(:);
     end
     [W, ~, ~] = STAPLE(stapleParam);
 
-    % get segmentations dimensions
-    imageDims = size(segmentations{1});
-
-    % reshape to get the ground truth segmentation
+    % Reshape to get the ground truth segmentation.
     gtSegmentation = reshape((W >= .5), imageDims);
 end