colon_reconstruction_dataset

This repository contains brief introdcution of simulated data for colon 3D reconstruction and the dataset download link

This dataset contains 15 cases of simulated stereo colonoscopic images with ground truth of camera poses (left camera poses, right camera poses and rotations).

In each folder named Case#, its subfolder "left" contains the left camera images and "right" contains the right camera images. And three "txt" for mat files are left camera poses, right camera poses and rotations, the optical center of the first frame camera is used as the origin point of the global space.

Camera calibration parameters: fx = 232.5044678; % unit in pixel fy = 232.5044678; cx = 240.0; cy = 320.0; baseline = 4.5; %unit in milimeter

Our developed simulator and code:

https://drive.google.com/drive/folders/1cypaTsHpi7TRVKI5cYvzk1UfpmdcOEts?usp=sharing

the link to dataset

https://studentutsedu-my.sharepoint.com/:f:/g/personal/shuai_zhang_alumni_uts_edu_au/EgYXJSm-4HdEj7ZnO6S1eSUBuS0wDmjRAJpbx30VOgJhjQ?e=b7ktTC

If you use the developed simulator and datasets in your papers, please cite our paper named "A Template-based 3D Reconstruction of Colon Structures and Textures from Stereo Colonoscopic Images", thank you very much!

For the usgae of related parameters in the developed simulator: The example to obtain camera intrinsic parameters, camera extrinsic parameters and point cloud of one frame:

focal_length = 4.969783;

sensor_width = 10.26;

sensor_height = 7.695;

cols = 320; % image width

rows = 240; % image height

fx = focal_length * cols / sensor_width; % unit in pixel

fy = focal_length * rows / sensor_height;

cx = cols/2.0;

cy = rows/2.0;

img_rgb = cell(1,num);

depth_exr = cell(1,num);

for i = 1:num

img_rgb{i} = imread(['path\SUK_L',num2str(i,'%05d'),'.png']);

depth_exr{i} = exrread(['path\SUK_L_depth',num2str(i,'%05d'),'.exr']); end

scan_gt = cell(1,num);

depth_scale = 5.0;

for i = 1:num

xyzPoints = zeros(rows, cols, 3);

for v = 1:rows % rows

for u = 1:cols % cols

    d = depth_exr{i}(v,u,1);
    
    if d == 0
    
        continue;
        
    end
    
    depth_pixel = depth_scale * double(d);
    
    xyzPoints(v,u,3) = depth_pixel;
    
    xyzPoints(v,u,1) = (u - cx)*depth_pixel/fx; % x coordinates
    
    xyzPoints(v,u,2) = (v - cy)*depth_pixel/fy; % y coordinates
    
end

end

ptCloudOut = pointCloud(xyzPoints, 'Color', img_rgb{i});

scan_gt{i} = ptCloudOut; end

% transform quaternion from the unity left handed space to matlab right handed space

% y direction is opposite

% [q0, q1, q2, q3]-->[q0, -q1, q2, -q3] under y direction is opposite

unity:

quat = [q0, q1, q2, q3];

quat(2) = quat(2)*(-1);

quat(4) = quat(4)*(-1);

rotm = quat2rotm(quat);

% tranform translation from unity left handed space to matlab right handed space

% [x,-y,z]-->[x,y,z] under x direction is opposite

transt = [x,y,z]

transt(2) = transt(2) * (-1);

% "rotm" is the camera's pose in the world space, so rotm's transpose can transform the camera's

% scan back to its original pose in the world space

grdth = [rotm', zeros(3,1); transt*10, 1]; % convert cm to mm, the colon model is in mm unit

pose = affine3d(grdth); %pose format in matlab, it transforms the local point cloud into the global colon model space