提取边界内的图像区域

Question

我必须做一个项目，使用二维CT图像和分割肝脏和肿瘤在Matlab中使用（仅）。最初我必须单独分割肝脏区域。我使用区域生长来分割肝脏。它获取种子点作为输入。

输出是一个具有肝脏区域边界的图像。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。由于我是新用户，因此我不允许发布图片。如果你确实需要图片，我会邮寄给你。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)!']) 

Answer 1

如果我理解正确的话，你有肾虚的边界的二进制图像，现在需要的边界内设置为1秒。要做到这一点，您可以使用imfill()功能，打开“孔”设置。

BW2 = imfill(BW,'holes'); 

编辑：看看代码，它似乎它做你想要的东西。

% Outputs: 
% J: Binary mask (with the same size as the input image) indicating 
%  1 (true) for associated pixel/voxel and 0 (false) for outside 

，所以你只需要获得第二输出，以及：

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与您的分割区域的二进制图像。

EDIT2：

一旦你的二进制图像im，你可以简单地使用元素方式乘法删除分割区域外的原始图片的所有部分。

SEG = IR.*im; 
imshow(SEG,[]) 

EDIT3：

对于3D影像，需要手动，而不是使用鼠标来指定坐标。这是因为鼠标只给我们2个坐标（x和y），而你需要3个（x，y和z）。所以通过查看图像找到你需要的坐标，然后选择一个合适的z坐标。

%Example coordinates, 
coordinates = [100 100 5] 
poly = regionGrowing(squeeze(IR), coordinates, 60, Inf, [], true, false);