matlab如何计算CT图像原始图像和重建图像的SSIM代码
时间: 2024-10-20 17:06:27 浏览: 29
MATLAB 中可以使用 Image Processing Toolbox 的 Structural Similarity Index (SSIM) 函数来计算 CT 图像(原图像和重建图像)之间的结构相似度。首先,你需要安装该工具箱。下面是基本的步骤和代码示例:
1. 确保已经加载了所需的库:
```matlab
% 加载Image Processing Toolbox
iptsetpref('Imshow', 'BorderVisible', 'off'); % 隐藏imshow窗口边框
```
2. 定义 SSIM 函数:
```matlab
function ssim_val = calculate_ssim(original, reconstructed)
% 计算两个输入图像的SSIM值
if ~isequal(size(original), size(reconstructed))
error('Original and reconstructed images must have the same dimensions');
end
[ssim_val, map] = ssim(original, reconstructed);
end
```
3. 读取和预处理原始图像和重建图像(假设它们分别是 `original_ct` 和 `reconstructed_ct`):
```matlab
% 假设原始CT图像和重建CT图像在同一文件夹下
[original_path, ~] = uigetfile({'*.dcm'; '*.png'; '*.jpg'}, 'Select Original CT Image');
original_ct = imread(original_path); % 或根据实际文件格式读取
[reconstructed_path, ~] = uigetfile({'*.dcm'; '*.png'; '*.jpg'}, 'Select Reconstructed CT Image');
reconstructed_ct = imread(reconstructed_path); % 同样读取
% 对图像进行必要的预处理,如灰度化、归一化等
original_ct = rgb2gray(original_ct);
reconstructed_ct = rgb2gray(reconstructed_ct);
original_ct = imresize(original_ct, size(reconstructed_ct)); % 如果尺寸不同,先调整大小
```
4. 调用 `calculate_ssim` 函数并显示结果:
```matlab
ssim_value = calculate_ssim(original_ct, reconstructed_ct);
disp(['The SSIM value between original and reconstructed CT image is: ', num2str(ssim_value)]);
```
5.
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