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)!'])

最佳答案 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“孔”设置的

imfill()功能.

BW2 = imfill(BW,'holes');

编辑：看看代码,似乎它已经做了你想要的.

% 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是带有分段区域的二进制图像.

EDIT2：

一旦你有二进制图像im,你可以简单地使用逐元素乘法来删除分割区域外的orignal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,只需查看图像,然后选择合适的z坐标即可找到所需的坐标.

%Example coordinates,

coordinates = [100 100 5]

poly = regionGrowing(squeeze(IR), coordinates, 60, Inf, [], true, false);