我必须使用2D CT图像进行一个项目，并使用Matlab（仅）对肝脏和肿瘤进行分割。最初我必须单独分割肝脏区域。我使用区域生长进行肝脏分割。它获得种子点作为输入。
输出是具有肝区边界的图像。现在我需要仅由边界包围的区域。
我的程序有一个主程序和一个regionGrowing.m函数。因为我是新用户，所以不允许发布图片。如果你确实需要图像，我会给你发邮件。请帮助我。
% mainreg.m
IR=imread('nfliver5.jpg');
figure, imshow(IR), hold all
poly = regionGrowing(IR,[],15,1200); % click somewhere inside the liver
plot(poly(:,1), poly(:,2), 'LineWidth', 2, 'Color', [1 1 1])
%regionGrowing.m
function [P, J] = regionGrowing(cIM, initPos, thresVal, maxDist, tfMean, tfFillHoles, tfSimplify)
% REGIONGROWING Region growing algorithm for 2D/3D grayscale images
%
% Syntax:
% P = regionGrowing();
% P = regionGrowing(cIM);
% P = regionGrowing(cIM, initPos)
% P = regionGrowing(..., thresVal, maxDist, tfMean, tfFillHoles, tfSimpl)
% [P, J] = regionGrowing(...);
%
% Inputs:
% cIM: 2D/3D grayscale matrix {current image}
% initPos: Coordinates for initial seed position {ginput position}
% thresVal: Absolute threshold level to be included {5% of max-min}
% maxDist: Maximum distance to the initial position in [px] {Inf}
% tfMean: Updates the initial value to the region mean (slow) {false}
% tfFillHoles: Fills enclosed holes in the binary mask {true}
% tfSimplify: Reduces the number of vertices {true, if dpsimplify exists}
%
% Outputs:
% P: VxN array (with V number of vertices, N number of dimensions)
% P is the enclosing polygon for all associated pixel/voxel
% J: Binary mask (with the same size as the input image) indicating
% 1 (true) for associated pixel/voxel and 0 (false) for outside
%
% Examples:
% % 2D Example
% load example
% figure, imshow(cIM, [0 1500]), hold all
% poly = regionGrowing(cIM, [], 300); % click somewhere inside the lungs
% plot(poly(:,1), poly(:,2), 'LineWidth', 2)
%
% % 3D Example
% load mri
% poly = regionGrowing(squeeze(D), [66,55,13], 60, Inf, [], true, false);
% plot3(poly(:,1), poly(:,2), poly(:,3), 'x', 'LineWidth', 2)
%
% Requirements:
% TheMathWorks Image Processing Toolbox for bwboundaries() and axes2pix()
% Optional: Line Simplification by Wolfgang Schwanghart to reduce the
% number of polygon vertices (see the MATLAB FileExchange)
%
% Remarks:
% The queue is not preallocated and the region mean computation is slow.
% I haven't implemented a preallocation nor a queue counter yet for the
% sake of clarity, however this would be of course more efficient.
%
% Author:
% Daniel Kellner, 2011, braggpeaks{}googlemail.com
% History: v1.00: 2011/08/14
% error checking on input arguments
if nargin > 7
error('Wrong number of input arguments!')
end
if ~exist('cIM', 'var')
himage = findobj('Type', 'image');
if isempty(himage) || length(himage) > 1
error('Please define one of the current images!')
end
cIM = get(himage, 'CData');
end
if ~exist('initPos', 'var') || isempty(initPos)
himage = findobj('Type', 'image');
if isempty(himage)
himage = imshow(cIM, []);
end
% graphical user input for the initial position
p = ginput(1);
% get the pixel position concerning to the current axes coordinates
initPos(1) = round(axes2pix(size(cIM, 2), get(himage, 'XData'), p(2)));
initPos(2) = round(axes2pix(size(cIM, 1), get(himage, 'YData'), p(1)));
end
if ~exist('thresVal', 'var') || isempty(thresVal)
thresVal = double((max(cIM(:)) - min(cIM(:)))) * 0.05;
end
if ~exist('maxDist', 'var') || isempty(maxDist)
maxDist = Inf;
end
if ~exist('tfMean', 'var') || isempty(tfMean)
tfMean = false;
end
if ~exist('tfFillHoles', 'var')
tfFillHoles = true;
end
if isequal(ndims(cIM), 2)
initPos(3) = 1;
elseif isequal(ndims(cIM),1) || ndims(cIM) > 3
error('There are only 2D images and 3D image sets allowed!')
end
[nRow, nCol, nSli] = size(cIM);
if initPos(1) < 1 || initPos(2) < 1 ||...
initPos(1) > nRow || initPos(2) > nCol
error('Initial position out of bounds, please try again!')
end
if thresVal < 0 || maxDist < 0
error('Threshold and maximum distance values must be positive!')
end
if ~isempty(which('dpsimplify.m'))
if ~exist('tfSimplify', 'var')
tfSimplify = true;
end
simplifyTolerance = 1;
else
tfSimplify = false;
end
% initial pixel value
regVal = double(cIM(initPos(1), initPos(2), initPos(3)));
% text output with initial parameters
disp(['RegionGrowing Opening: Initial position (' num2str(initPos(1))...
'|' num2str(initPos(2)) '|' num2str(initPos(3)) ') with '...
num2str(regVal) ' as initial pixel value!'])
% preallocate array
J = false(nRow, nCol, nSli);
% add the initial pixel to the queue
queue = [initPos(1), initPos(2), initPos(3)];
%%% START OF REGION GROWING ALGORITHM
while size(queue, 1)
% the first queue position determines the new values
xv = queue(1,1);
yv = queue(1,2);
zv = queue(1,3);
% .. and delete the first queue position
queue(1,:) = [];
% check the neighbors for the current position
for i = -1:1
for j = -1:1
for k = -1:1
if xv+i > 0 && xv+i <= nRow &&... % within the x-bounds?
yv+j > 0 && yv+j <= nCol &&... % within the y-bounds?
zv+k > 0 && zv+k <= nSli &&... % within the z-bounds?
any([i, j, k]) &&... % i/j/k of (0/0/0) is redundant!
~J(xv+i, yv+j, zv+k) &&... % pixelposition already set?
sqrt( (xv+i-initPos(1))^2 +...
(yv+j-initPos(2))^2 +...
(zv+k-initPos(3))^2 ) < maxDist &&... % within distance?
cIM(xv+i, yv+j, zv+k) <= (regVal + thresVal) &&...% within range
cIM(xv+i, yv+j, zv+k) >= (regVal - thresVal) % of the threshold?
% current pixel is true, if all properties are fullfilled
J(xv+i, yv+j, zv+k) = true;
% add the current pixel to the computation queue (recursive)
queue(end+1,:) = [xv+i, yv+j, zv+k];
if tfMean
regVal = mean(mean(cIM(J > 0))); % --> slow!
end
end
end
end
end
end
%%% END OF REGION GROWING ALGORITHM
% loop through each slice, fill holes and extract the polygon vertices
P = [];
for cSli = 1:nSli
if ~any(J(:,:,cSli))
continue
end
% use bwboundaries() to extract the enclosing polygon
if tfFillHoles
% fill the holes inside the mask
J(:,:,cSli) = imfill(J(:,:,cSli), 'holes');
B = bwboundaries(J(:,:,cSli), 8, 'noholes');
else
B = bwboundaries(J(:,:,cSli));
end
newVertices = [B{1}(:,2), B{1}(:,1)];
% simplify the polygon via Line Simplification
if tfSimplify
newVertices = dpsimplify(newVertices, simplifyTolerance);
end
% number of new vertices to be added
nNew = size(newVertices, 1);
% append the new vertices to the existing polygon matrix
if isequal(nSli, 1) % 2D
P(end+1:end+nNew, :) = newVertices;
else % 3D
P(end+1:end+nNew, :) = [newVertices, repmat(cSli, nNew, 1)];
end
end
% text output with final number of vertices
disp(['RegionGrowing Ending: Found ' num2str(length(find(J)))...
' pixels within the threshold range (' num2str(size(P, 1))...
' polygon vertices)!'])
答案 0 :(得分：2)
如果我理解正确，你有一个肾脏边界的二进制图像，现在需要将边界内部设置为1s。为此，您可以使用带有'holes'设置的imfill()功能。
BW2 = imfill(BW,'holes');
% Outputs:
% J: Binary mask (with the same size as the input image) indicating
% 1 (true) for associated pixel/voxel and 0 (false) for outside
所以你只需要得到第二个输出：
IR=imread('nfliver5.jpg');
figure, imshow(IR), hold all
[poly im] = regionGrowing(IR,[],15,1200); % click somewhere inside the liver
imshow(im,[])
现在im是包含您的分段区域的二进制图像。
EDIT2：
获得二进制图像im后，您可以简单地使用逐元素乘法来移除分割区域外的原始图像的所有部分。
SEG = IR.*im;
imshow(SEG,[])
EDIT3：
对于3D图像，您需要手动指定坐标，而不是使用鼠标。这是因为鼠标只给我们2个坐标（x和y），你需要3个（x，y和z）。因此，只需通过查看图像找到所需的坐标，然后选择合适的z坐标。
%Example coordinates,
coordinates = [100 100 5]
poly = regionGrowing(squeeze(IR), coordinates, 60, Inf, [], true, false);