使用SimpleITK批量计算医学图像分割的mask体积，病灶体积

使用SimpleITK计算如下所示的病灶标注的整体体积。

可以在该代码的基础上，增加写入excel表的操作，这样就可以把模型推理前的体积和模型推理后的体积都写入excel表，然后进行一系列分析。

1 计算ROI病灶体积

用SimpleITK包进行ROI/病灶体积的计算

import SimpleITK as sitk
import numpy as np

def calculate_volume(mask_image_path):
    # 读取分割结果的图像文件
    mask_image = sitk.ReadImage(mask_image_path)

    # 获取图像的大小、原点和间距
    size = mask_image.GetSize()
    origin = mask_image.GetOrigin()
    spacing = mask_image.GetSpacing()

    # 将 SimpleITK 图像转换为 NumPy 数组
    mask_array = sitk.GetArrayFromImage(mask_image)

    # 计算非零像素的数量
    non_zero_voxels = (mask_array > 0).sum()

    # 计算像素的体积（以立方毫米为单位）
    voxel_volume_mm3 = spacing[0] * spacing[1] * spacing[2]

    # 计算体积（以 mm³ 为单位）
    volume_mm3 = non_zero_voxels * voxel_volume_mm3

    # 如果需要以其他单位（例如 cm³）显示，请进行适当的单位转换
    volume_cm3 = volume_mm3 / 1000.0

    return size,spacing,non_zero_voxels,volume_cm3

maskFilePath = "./dataset/split_2_41/train/Mask/sub-strokecase0001_ses-0001_msk_reg.nii.gz"
size,spacing,non_zero_voxels,roi_volume = calculate_volume(maskFilePath)

print("================================")
print(size,spacing,non_zero_voxels)

print(f'ROI 或病灶的体积为 {roi_volume} cm³')

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37

测试结果：

================================
(97, 113, 97) (2.0, 2.0, 2.0) 1446
ROI 或病灶的体积为 11.568 cm³

2，写入excel中

写入excel中：表格形式如下：

代码如下：

import SimpleITK as sitk
import numpy as np
import os
import pandas as pd
import openpyxl

def toexcel(maskfilepath,excelfilepath):
    maskFilePath = maskfilepath
    excel_file_path = excelfilepath

    file_names = []
    sizes = []
    spacings = []
    non_zero_voxels = []
    roi_volumes = []

    for file_name in os.listdir(maskFilePath):
        if file_name.endswith('.nii.gz'):  # Assuming your files have this extension
            file_path = os.path.join(maskFilePath, file_name)

            # Assuming your calculate_volume function returns a tuple (size, spacing, non_zero_voxels, roi_volume)
            size, spacing, non_zero_voxel, roi_volume = calculate_volume(file_path)

            file_names.append(file_name)
            sizes.append(size)
            spacings.append(spacing)
            non_zero_voxels.append(non_zero_voxel)
            roi_volumes.append(roi_volume)

    print(file_names, spacings, non_zero_voxels, roi_volumes)

    # Create a DataFrame from the lists:
    data = {
        'File Name': file_names,
        'Size': sizes,
        'Spacing': spacings,
        'Non-Zero Voxels': non_zero_voxels,
        'ROI Volume': roi_volumes
    }

    df = pd.DataFrame(data)
    df.to_excel(excel_file_path, index=False, header=['File Name', 'Size', 'Spacing', 'Non-Zero', 'ROI Volume/Ml'])
    print('完成')
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44