[小技巧]把.nii.gz文件从3D图像变成2D图像

2024-06-02 03:17| 来源: 网络整理| 查看: 265

问题

很多时候3D网络由于参数量大，不好训练，一般转换成2D图像使用2D网络进行训练，当然也会有比如切片上下文信息丢失的问题，抛开不谈。（2D->2.5D）在这里插入代码片

代码

下面是读取.nii.gz文件，然后进行窗口窗位变换，得到变换后的数值，然后在保存为2D图片。

import SimpleITK as sitk import os import nibabel as nib import numpy as np import matplotlib.pyplot as plt import pydicom def load_nifti(file_path): img = nib.load(file_path) img_data = img.get_fdata() return img_data def adjust_window(image, window_center, window_width): image_min = window_center - window_width / 2.0 image_max = window_center + window_width / 2.0 adjusted_image = np.clip(image, image_min, image_max) adjusted_image = (adjusted_image - image_min) / (image_max - image_min) return adjusted_image def save_slices_as_png(image_path, output_folder): # Load the NIfTI image image = sitk.ReadImage(image_path) # mask = sitk.ReadImage(mask_path) # 获取数组表示 image_array = sitk.GetArrayFromImage(image) # mask_array = sitk.GetArrayFromImage(mask) # Extract file name without extension file_name = os.path.basename(image_path).split(".")[0] # Create output folder if it doesn't exist os.makedirs(output_folder, exist_ok=True) # Iterate through slices and save as .png for i in range(image_array.shape[0]): # Get the ith slice slice_data = image_array[i, :, :] # Adjust CT window adjusted_slice = adjust_window(slice_data, window_center, window_width) # Save as .png png_path = os.path.join(output_folder, f"{file_name}_{i}.png") plt.imsave(png_path, adjusted_slice, cmap='gray') if __name__ == "__main__": data_folder = r"D:\Download\data\data" # Set the CT window parameters window_center = 30 window_width = 400 # Process image folder image_folder = os.path.join(data_folder, "images") mask_folder = os.path.join(data_folder, "masks") for image_file in os.listdir(mask_folder): image_path = os.path.join(image_folder, image_file) save_slices_as_png(image_path, r"D:/Download/data/data/2D/images") # Process mask folder for mask_file in os.listdir(mask_folder): mask_path = os.path.join(mask_folder, mask_file) save_slices_as_png(mask_path, r"D:/Download/data/data/2D/masks")

可以看到很多图片对应的mask文件是全黑的，说明其中没有病灶区域，为了除去这些图片，可以用下面这段代码。

import os import cv2 import numpy as np def is_black_mask(mask_array): return np.all(mask_array == 0) def remove_images_with_black_masks(image_folder, mask_folder): for image_file in os.listdir(image_folder): image_path = os.path.join(image_folder, image_file) mask_path = os.path.join(mask_folder, image_file) # 读取标签 mask = cv2.imread(mask_path, cv2.IMREAD_GRAYSCALE) # 检查标签是否全是黑色 if is_black_mask(mask): # 删除对应的图像和标签 os.remove(image_path) os.remove(mask_path) if __name__ == "__main__": image_folder = "D:/Download/data/data/2D/images" mask_folder = "D:/Download/data/data/2D/masks" remove_images_with_black_masks(image_folder, mask_folder)

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