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python nii ssim

时间: 2025-01-07 09:37:20 浏览: 55

### 计算NIfTI文件的结构相似性指数(SSIM) 为了在 Python 中计算 NIfTI 图像之间的 SSIM 值，可以采用 `nibabel` 库来加载 nii 文件，并利用 `skimage.metrics.structural_similarity` 函数来进行 SSIM 的评估。首先安装所需的库： ```bash pip install nibabel scikit-image numpy ``` 下面是一个完整的代码示例用于读取两个 NIfTI 文件并计算它们之间 SSIM: ```python import nibabel as nib from skimage.metrics import structural_similarity as ssim import numpy as np def load_nifti_data(file_path): img = nib.load(file_path) data = img.get_fdata() return data def calculate_ssim_3d(imageA, imageB): scores = [] for i in range(imageA.shape[-1]): score, _ = ssim( imageA[..., i], imageB[..., i], win_size=7, multichannel=False, gaussian_weights=True, sigma=1.5, use_sample_covariance=False, data_range=imageA.max() - imageA.min()) scores.append(score) average_score = sum(scores)/len(scores) return average_score, scores file_path_A = 'path_to_first_image.nii' file_path_B = 'path_to_second_image.nii' img_data_A = load_nifti_data(file_path_A)[^2] img_data_B = load_nifti_data(file_path_B)[^2] average_ssim, slice_wise_scores = calculate_ssim_3d(img_data_A, img_data_B)[^3] print(f'Average SSIM Score: {average_ssim}') print('Slice-wise Scores:', slice_wise_scores) ``` 此脚本定义了一个函数 `calculate_ssim_3d()` 来逐片计算三维体积数据间的 SSIM 并返回平均得分以及每一片的具体分数。注意这里假设输入的是单通道灰度图像；如果处理多模态或多通道的数据，则需调整参数设置[^4]。

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