医疗图像ROI区域根据标注自动提取

import numpy as np
import torchio as tio
from torch.utils.data import DataLoader
import torch
import nibabel as nib

z=0
while z<999:
    z = z+1

    subject = tio.Subject(
        chest_ct=tio.ScalarImage(fr'C:UsersAdminDesktopEGFR totalEGFRzhongnewdata1data{z}.nii.gz'),
        heart_mask=tio.LabelMap(fr'C:UsersAdminDesktopEGFR totalEGFRzhongnewmask1mask{z}.nii.gz'),
    )
    subject.chest_ct.shape
    transform = tio.CropOrPad(
        # (96, 96, 96),
        mask_name='heart_mask',

    )
    transformed = transform(subject)
    transformed.chest_ct.shape

    a = transformed.get_first_image()
    a = a.numpy()
    x = a[0]
    print(a[0].shape)
    img_t1 = nib.Nifti1Image(x, np.eye(4))
    nib.save(img_t1, f'output{z}.nii.gz')  # 将之保存为nii查看