Added DICOM conversion script (#3095)
* Added DICOM conversion script * Updated changelog * Fixed strip to rstrip * Fixed some detected issues * Removed extra variable, updated README.mdmain
Boris Sekachev
5 years ago
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GitHub
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# Description
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The script is used to convert some kinds of DICOM data to regular images.
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Then you can annotate these images on CVAT and get a segmentation mask.
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The conversion script was tested on CT, MT and some multi-frame DICOM data.
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DICOM files with series (multi-frame) are saved under the same name with a number postfix: 001, 002, 003, etc.
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# Installation
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```bash
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python3 -m venv .env
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. .env/bin/activate
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pip install -r requirements.txt
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```
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# Running
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```
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. .env/bin/activate # if not activated
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python script.py input_data output_data
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```
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numpy==1.20.2
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Pillow==8.2.0
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pydicom==2.1.2
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tqdm==4.60.0
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# Copyright (C) 2021 Intel Corporation
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#
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# SPDX-License-Identifier: MIT
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import os
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import argparse
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import logging
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from glob import glob
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import numpy as np
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from tqdm import tqdm
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from PIL import Image
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from pydicom import dcmread
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from pydicom.pixel_data_handlers.util import convert_color_space
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# Script configuration
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(message)s')
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parser = argparse.ArgumentParser(description='The script is used to convert some kinds of DICOM (.dcm) files to regular image files (.png)')
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parser.add_argument('input', type=str, help='A root directory with medical data files in DICOM format. The script finds all these files based on their extension')
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parser.add_argument('output', type=str, help='Where to save converted files. The script repeats internal directories structure of the input root directory')
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args = parser.parse_args()
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class Converter:
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def __init__(self, filename):
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with dcmread(filename) as ds:
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self._pixel_array = ds.pixel_array
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self._photometric_interpretation = ds.PhotometricInterpretation
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self._min_value = ds.pixel_array.min()
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self._max_value = ds.pixel_array.max()
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self._depth = ds.BitsStored
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logging.debug('File: {}'.format(filename))
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logging.debug('Photometric interpretation: {}'.format(self._photometric_interpretation))
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logging.debug('Min value: {}'.format(self._min_value))
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logging.debug('Max value: {}'.format(self._max_value))
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logging.debug('Depth: {}'.format(self._depth))
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try:
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self._length = ds["NumberOfFrames"].value
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except KeyError:
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self._length = 1
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def __len__(self):
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return self._length
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def __iter__(self):
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if self._length == 1:
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self._pixel_array = np.expand_dims(self._pixel_array, axis=0)
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for pixel_array in self._pixel_array:
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# Normalization to an output range 0..255, 0..65535
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pixel_array = pixel_array - self._min_value
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pixel_array = pixel_array.astype(int) * (2 ** self._depth - 1)
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pixel_array = pixel_array // (self._max_value - self._min_value)
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# In some cases we need to convert colors additionally
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if 'YBR' in self._photometric_interpretation:
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pixel_array = convert_color_space(pixel_array, self._photometric_interpretation, 'RGB')
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if self._depth == 8:
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image = Image.fromarray(pixel_array.astype(np.uint8))
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elif self._depth == 16:
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image = Image.fromarray(pixel_array.astype(np.uint16))
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else:
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raise Exception('Not supported depth {}'.format(self._depth))
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yield image
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def main(root_dir, output_root_dir):
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dicom_files = glob(os.path.join(root_dir, '**', '*.dcm'), recursive = True)
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if not len(dicom_files):
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logging.info('DICOM files are not found under the specified path')
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else:
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logging.info('Number of found DICOM files: ' + str(len(dicom_files)))
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pbar = tqdm(dicom_files)
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for input_filename in pbar:
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pbar.set_description('Conversion: ' + input_filename)
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input_basename = os.path.basename(input_filename)
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output_subpath = os.path.relpath(os.path.dirname(input_filename), root_dir)
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output_path = os.path.join(output_root_dir, output_subpath)
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output_basename = '{}.png'.format(os.path.splitext(input_basename)[0])
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output_filename = os.path.join(output_path, output_basename)
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if not os.path.exists(output_path):
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os.makedirs(output_path)
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try:
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iterated_converter = Converter(input_filename)
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length = len(iterated_converter)
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for i, image in enumerate(iterated_converter):
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if length == 1:
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image.save(output_filename)
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else:
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filename_index = str(i).zfill(len(str(length)))
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list_output_filename = '{}_{}.png'.format(os.path.splitext(output_filename)[0], filename_index)
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image.save(list_output_filename)
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except Exception as ex:
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logging.error('Error while processing ' + input_filename)
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logging.error(ex)
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if __name__ == '__main__':
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input_root_path = os.path.abspath(args.input.rstrip(os.sep))
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output_root_path = os.path.abspath(args.output.rstrip(os.sep))
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logging.info('From: {}'.format(input_root_path))
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logging.info('To: {}'.format(output_root_path))
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main(input_root_path, output_root_path)
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