未验证 提交 f267f8ae 编写于 作者: B Boris Sekachev 提交者: GitHub

Added DICOM conversion script (#3095)

* Added DICOM conversion script

* Updated changelog

* Fixed strip to rstrip

* Fixed some detected issues

* Removed extra variable, updated README.md
上级 8a635b11
......@@ -11,6 +11,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
- Documentation on mask annotation (<https://github.com/openvinotoolkit/cvat/pull/3044>)
- Hotkeys to switch a label of existing object or to change default label (for objects created with N) (<https://github.com/openvinotoolkit/cvat/pull/3070>)
- A script to convert some kinds of DICOM files to regular images (<https://github.com/openvinotoolkit/cvat/pull/3095>)
### Changed
......
# Description
The script is used to convert some kinds of DICOM data to regular images.
Then you can annotate these images on CVAT and get a segmentation mask.
The conversion script was tested on CT, MT and some multi-frame DICOM data.
DICOM files with series (multi-frame) are saved under the same name with a number postfix: 001, 002, 003, etc.
# Installation
```bash
python3 -m venv .env
. .env/bin/activate
pip install -r requirements.txt
```
# Running
```
. .env/bin/activate # if not activated
python script.py input_data output_data
```
numpy==1.20.2
Pillow==8.2.0
pydicom==2.1.2
tqdm==4.60.0
# Copyright (C) 2021 Intel Corporation
#
# SPDX-License-Identifier: MIT
import os
import argparse
import logging
from glob import glob
import numpy as np
from tqdm import tqdm
from PIL import Image
from pydicom import dcmread
from pydicom.pixel_data_handlers.util import convert_color_space
# Script configuration
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(message)s')
parser = argparse.ArgumentParser(description='The script is used to convert some kinds of DICOM (.dcm) files to regular image files (.png)')
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')
parser.add_argument('output', type=str, help='Where to save converted files. The script repeats internal directories structure of the input root directory')
args = parser.parse_args()
class Converter:
def __init__(self, filename):
with dcmread(filename) as ds:
self._pixel_array = ds.pixel_array
self._photometric_interpretation = ds.PhotometricInterpretation
self._min_value = ds.pixel_array.min()
self._max_value = ds.pixel_array.max()
self._depth = ds.BitsStored
logging.debug('File: {}'.format(filename))
logging.debug('Photometric interpretation: {}'.format(self._photometric_interpretation))
logging.debug('Min value: {}'.format(self._min_value))
logging.debug('Max value: {}'.format(self._max_value))
logging.debug('Depth: {}'.format(self._depth))
try:
self._length = ds["NumberOfFrames"].value
except KeyError:
self._length = 1
def __len__(self):
return self._length
def __iter__(self):
if self._length == 1:
self._pixel_array = np.expand_dims(self._pixel_array, axis=0)
for pixel_array in self._pixel_array:
# Normalization to an output range 0..255, 0..65535
pixel_array = pixel_array - self._min_value
pixel_array = pixel_array.astype(int) * (2 ** self._depth - 1)
pixel_array = pixel_array // (self._max_value - self._min_value)
# In some cases we need to convert colors additionally
if 'YBR' in self._photometric_interpretation:
pixel_array = convert_color_space(pixel_array, self._photometric_interpretation, 'RGB')
if self._depth == 8:
image = Image.fromarray(pixel_array.astype(np.uint8))
elif self._depth == 16:
image = Image.fromarray(pixel_array.astype(np.uint16))
else:
raise Exception('Not supported depth {}'.format(self._depth))
yield image
def main(root_dir, output_root_dir):
dicom_files = glob(os.path.join(root_dir, '**', '*.dcm'), recursive = True)
if not len(dicom_files):
logging.info('DICOM files are not found under the specified path')
else:
logging.info('Number of found DICOM files: ' + str(len(dicom_files)))
pbar = tqdm(dicom_files)
for input_filename in pbar:
pbar.set_description('Conversion: ' + input_filename)
input_basename = os.path.basename(input_filename)
output_subpath = os.path.relpath(os.path.dirname(input_filename), root_dir)
output_path = os.path.join(output_root_dir, output_subpath)
output_basename = '{}.png'.format(os.path.splitext(input_basename)[0])
output_filename = os.path.join(output_path, output_basename)
if not os.path.exists(output_path):
os.makedirs(output_path)
try:
iterated_converter = Converter(input_filename)
length = len(iterated_converter)
for i, image in enumerate(iterated_converter):
if length == 1:
image.save(output_filename)
else:
filename_index = str(i).zfill(len(str(length)))
list_output_filename = '{}_{}.png'.format(os.path.splitext(output_filename)[0], filename_index)
image.save(list_output_filename)
except Exception as ex:
logging.error('Error while processing ' + input_filename)
logging.error(ex)
if __name__ == '__main__':
input_root_path = os.path.abspath(args.input.rstrip(os.sep))
output_root_path = os.path.abspath(args.output.rstrip(os.sep))
logging.info('From: {}'.format(input_root_path))
logging.info('To: {}'.format(output_root_path))
main(input_root_path, output_root_path)
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