如何使用python划分半个pydicom文件（图像）？

Question

I have a lot of images (pydicom files). I would like to divide in half. From 1 image, I would like 2 images: part left and part right.

Input: 1000x1000 Output: 500x1000 (width x height).

Currently, I can only read a file.

ds = pydicom.read_file(image_fps[0]) # read dicom image from filepath 

First part, I would like to put half in one folder and the other half to second. This is what I have: enter image description here This is what I want: enter image description here

I use Mask-RCNN to object localization problem. I would like crop 50% of image size (pydicom file).

EDIT1:

import SimpleITK as sitk
    filtered_image = sitk.GetImageFromArray(left_part)
    sitk.WriteImage(filtered_image, '/home/wojtek/Mask/nnna.dcm', True)

I have dicom file, but I can't display it.

this transfer syntax JPEG 2000 Image Compression (Lossless Only), can not be read because Pillow lacks the jpeg 2000 decoder plugin

Answer 1

Once you have executed pydicom.dcm_read() your pixel data is available at ds.pixel_array . You can just slice the data you want and save it with any suitable library. In this example I will be using matplotlib as I also use that for verifying whether my slicing is correct. Adjust to your needs obviously, one thing you need to do is generate the correct path/filenames for saving. Have fun! (this script assumes the filepaths are available in a paths variable)

import pydicom
import matplotlib

# for testing if the slice is correct
from matplotlib import pyplot as plt

for path in paths:
    # read the dicom file
    ds = pydicom.dcmread(path)

    # find the shape of your pixel data
    shape = ds.pixel_array.shape
    # get the half of the x dimension. For the y dimension use shape[0]
    half_x = int(shape[1] / 2)

    # slice the halves
    # [first_axis, second_axis] so [:,:half_x] means slice all from first axis, slice 0 to half_x from second axis
    left_part  = ds.pixel_array[:, :half_x]
    right_part = ds.pixel_array[:,half_x:]

    # to check whether the slices are correct, matplotlib can be convenient
    # plt.imshow(left_part); do not do this in the loop

    # save the files, see the documentation for matplotlib if you want a different format
    # bmp, png are surely supported

    path_to_left_image = 'generate\the\path\and\filename\for\the\left\image.bmp'
    path_to_right_image = 'generate\the\path\and\filename\for\the\right\image.bmp'
    matplotlib.image.imsave(path_to_left_image, left_part)
    matplotlib.image.imsave(path_to_right_image, right_part)

If you want to save the DICOM files keep in mind that they may not be valid DICOM if you do not update the appropriate data. For instance the SOP Instance UID is technically not allowed to be the same as in the original DICOM file, or any other SOP Instance UID for that matter. How important that is, is up to you.

With a script like below you can define named slices and split any dicom image file it finds in the supplied path into the appropriate slices.

import os
import pydicom
import numpy as np

def save_partials(parts, path_to_directory):
    """
    parts: list of tuples, each tuple specifying a name and a list of four slice offsets
    path_to_directory: path to directory containing dicom files
    any file with a .dcm extension will have its image data split into the specified slices and saved accordingly. 
    original file will not be modified
    """

    dir_content = [os.path.join(path_to_directory, item) for item in os.listdir(path_to_directory)]
    files = [i for i in dir_content if os.path.isfile(os.path.join(path_to_directory, i))]
    for file in files:
        root, extension = os.path.splitext(file)
        if extension.lower() != '.dcm':
            # not a .dcm file, continue with next iteration of loop
            continue
        for part in parts:
            ds = pydicom.read_file(file)
            if not isinstance(ds.pixel_array, np.ndarray):
                # no image data available
                continue
            part_name = part[0] 
            p = part[1] # slice list
            ds.PixelData = ds.pixel_array[p[0]:p[1], p[2]:p[3]].tobytes()
            ds.Rows = p[1] - p[0]
            ds.Columns = p[3] - p[2]
            ##
            ## Here you can modify any tags using ds.KeyWord
            ##
            new_file_name = "{r}-{pn}{ext}".format(r=root, pn=part_name, ext=extension)
            ds.save_as(new_file_name)
            print('saved {}'.format(new_file_name))


dir_path = '/home/wojtek/Mask'
parts = [('left', [0,512,0,256]),
         ('right', [0,512,256,512])]

save_partials(parts, dir_path)