如何读取多个堆栈 tiff 文件，应用函数并保存多个堆栈 tiff 文件？

如何解决如何读取多个堆栈 tiff 文件，应用函数并保存多个堆栈 tiff 文件？

背景

我使用预训练的 U-net 模型进行语义分割。它适用于一个堆栈 tiff 文件（具有多个切片的 CT 图像）。到目前为止我所做的：

##load pre-trained U-Net Model :
model.load_weights('/content/drive/MyDrive/Models saved/segmentation_cancer4.hdf5')
    
##import and preprocess new files:    
large_test_stack = tiff.imread('/content/drive/MyDrive/datasets/test/Test0.tif')
SIZE=256
all_img_patches = []
for img in range(large_test_stack.shape[0]):
    #print(img)     #just stop here to see all file names printed
    large_image = large_test_stack[img]
    patches_img = patchify(large_image,(SIZE,SIZE),step=SIZE)  #Step=256 for 256 patches means no overlap
        for i in range(patches_img.shape[0]):
        for j in range(patches_img.shape[1]):
            single_patch_img = patches_img[i,j,:,:]
            single_patch_img = (single_patch_img.astype('float32')) / 255.
            all_img_patches.append(single_patch_img)

images = np.expand_dims(normalize(np.array(all_img_patches),axis=1),3)

##apply model segmentation:   
prediction_other = (model.predict(images) > 0.9).astype(np.uint16) 

##save it as segmented volume.
from tifffile import imsave
imsave('/content/drive/MyDrive/datasets/results/Resultat24.tif',prediction_other)

问题

现在我想处理代表一百名患者的堆栈 tiff 文件列表，但我正在努力寻找一种简单的方法。我需要读取多个堆栈 tiff 文件，应用模型预测，然后将每个堆栈 tiff 预测保存在单独的文件夹中。

我怎么能做到这一点？