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matRad_rayTracing.m
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matRad_rayTracing.m
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function radDepthV = matRad_rayTracing(stf,ct,V,rot_coordsV,lateralCutoff)
% matRad visualization of two-dimensional dose distributions on ct
% including segmentation
%
% call
% radDepthV = matRad_rayTracing(stf,ct,V,rot_coordsV,lateralCutoff)
%
% input
% stf: matRad steering information struct of one beam
% ct: ct cube
% V: linear voxel indices e.g. of voxels inside patient.
% rot_coordsV coordinates in beams eye view inside the patient
% lateralCutoff: lateral cut off used for ray tracing
%
% output
% radDepthV: radiological depth inside the patient
%
% References
% [1] http://www.sciencedirect.com/science/article/pii/S1120179711001359
%
% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% Copyright 2015 the matRad development team.
%
% This file is part of the matRad project. It is subject to the license
% terms in the LICENSE file found in the top-level directory of this
% distribution and at https://github.com/e0404/matRad/LICENSES.txt. No part
% of the matRad project, including this file, may be copied, modified,
% propagated, or distributed except according to the terms contained in the
% LICENSE file.
%
% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% set up rad depth cube for results
radDepthCube = repmat({NaN*ones(ct.cubeDim)},ct.numOfCtScen);
% set up ray matrix direct behind last voxel
rayMx_bev_y = max(rot_coordsV(:,2)) + max([ct.resolution.x ct.resolution.y ct.resolution.z]);
rayMx_bev_y = rayMx_bev_y + stf.sourcePoint_bev(2);
% set up list with bev coordinates for calculation of radiological depth
coords = zeros(prod(ct.cubeDim),3);
coords(V,:) = rot_coordsV;
% calculate spacing of rays on ray matrix
rayMxSpacing = 1/sqrt(2) * min([ct.resolution.x ct.resolution.y ct.resolution.z]);
% define candidate ray matrix covering 1000x1000mm^2
numOfCandidateRays = 2 * ceil(500/rayMxSpacing) + 1;
candidateRayMx = zeros(numOfCandidateRays);
% define coordinates
[candidateRaysCoords_X,candidateRaysCoords_Z] = meshgrid(rayMxSpacing*[floor(-500/rayMxSpacing):ceil(500/rayMxSpacing)]);
% check which rays should be used
for i = 1:stf.numOfRays
ix = (candidateRaysCoords_X(:) - (1+rayMx_bev_y/stf.SAD)*stf.ray(i).rayPos_bev(1)).^2 + ...
(candidateRaysCoords_Z(:) - (1+rayMx_bev_y/stf.SAD)*stf.ray(i).rayPos_bev(3)).^2 ...
<= lateralCutoff^2;
candidateRayMx(ix) = 1;
end
% set up ray matrix
rayMx_bev = [candidateRaysCoords_X(logical(candidateRayMx(:))) ...
rayMx_bev_y*ones(sum(candidateRayMx(:)),1) ...
candidateRaysCoords_Z(logical(candidateRayMx(:)))];
% figure,
% for jj = 1:length(rayMx_bev)
% plot(rayMx_bev(jj,1),rayMx_bev(jj,3),'rx'),hold on
% end
% Rotation matrix. Transposed because of row vectors
rotMat_vectors_T = transpose(matRad_getRotationMatrix(stf.gantryAngle,stf.couchAngle));
% rotate ray matrix from bev to world coordinates
rayMx_world = rayMx_bev * rotMat_vectors_T;
% criterium for ray selection
raySelection = rayMxSpacing/2;
% perform ray tracing over all rays
for i = 1:size(rayMx_world,1)
% run siddon ray tracing algorithm
[~,l,rho,~,ixHitVoxel] = matRad_siddonRayTracer(stf.isoCenter, ...
ct.resolution, ...
stf.sourcePoint, ...
rayMx_world(i,:), ...
ct.cube);
% find voxels for which we should remember this tracing because this is
% the closest ray by projecting the voxel coordinates to the
% intersection points with the ray matrix and checking if the distance
% in x and z direction is smaller than the resolution of the ray matrix
scale_factor = (rayMx_bev_y - stf.sourcePoint_bev(2)) ./ ...
coords(ixHitVoxel,2);
x_dist = coords(ixHitVoxel,1).*scale_factor - rayMx_bev(i,1);
z_dist = coords(ixHitVoxel,3).*scale_factor - rayMx_bev(i,3);
ixRememberFromCurrTracing = x_dist > -raySelection & x_dist <= raySelection ...
& z_dist > -raySelection & z_dist <= raySelection;
if any(ixRememberFromCurrTracing) > 0
for j = 1:ct.numOfCtScen
% calc radiological depths
% eq 14
% It multiply voxel intersections with \rho values.
d = l .* rho{j}; %Note. It is not a number "one"; it is the letter "l"
% Calculate accumulated d sum.
dCum = cumsum(d)-d/2;
% write radiological depth for voxel which we want to remember
radDepthCube{j}(ixHitVoxel(ixRememberFromCurrTracing)) = dCum(ixRememberFromCurrTracing);
end
end
end
% only take voxel inside the patient
for i = 1:ct.numOfCtScen
radDepthV{i} = radDepthCube{i}(V);
end