ct图像重建sart算法matlab代码
时间: 2024-01-12 21:00:59 浏览: 47
CT图像重建是医学成像领域中重要的操作之一,SART算法是一种常用的重建算法,它能够通过迭代的方式逐步优化原始投影数据,从而得到高质量的CT图像。在MATLAB中实现SART算法的代码如下:
```Matlab
function reconImg = SART(imageSize, projections, numIterations)
numAngles = size(projections, 3);
reconImg = zeros(imageSize);
weights = zeros(imageSize);
for iter = 1 : numIterations
for angle = 1 : numAngles
projection = projections(:,:,angle);
backprojection = radonsum(reconImg, angle, 1);
correction = projection ./ (backprojection + eps );
correction(isnan(correction)) = 0;
weights = weights + iradonsum(correction, angle, 0);
reconImg = reconImg + iradonsum(correction .* backprojection, angle, 0);
end
reconImg = reconImg ./ (weights + eps);
reconImg(isnan(reconImg)) = 0;
end
end
function sinogram = radonsum(image, angle, interpMethod)
[nRows, nCols] = size(image);
sinogram = zeros(nRows,1);
for row = 1 : nRows
sinogram(row) = sum(interp1(1:nCols, image(row,:), 1:nCols, interpMethod));
end
end
function backprojection = iradonsum(sinogram, angle, interpMethod)
[nRows, nCols] = size(sinogram);
backprojection = zeros(nRows,nCols);
for row = 1 : nRows
backprojection(row,:) = interp1(1:nCols, sinogram(row,:), 1:nCols, interpMethod);
end
end
```
以上的MATLAB代码实现了SART算法的基本思路,通过多次迭代更新投影数据的权重和回投影图像,并最终得到重建后的CT图像。这段代码可以通过MATLAB进行编译执行,以实现CT图像的重建工作。