matlab如何计算CT图像原始图像和重建图像的SSIM代码

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：

% 加载Image Processing Toolbox
iptsetpref('Imshow', 'BorderVisible', 'off'); % 隐藏imshow窗口边框

2. 定义 SSIM 函数：

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`）：

% 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：

ssim_value = calculate_ssim(original_ct, reconstructed_ct);
disp(['The SSIM value between original and reconstructed CT image is: ', num2str(ssim_value)]);

5.