147 lines
4.3 KiB
Python
147 lines
4.3 KiB
Python
# Orthanc plugin for mammography
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# Copyright (C) 2024 Edouard Chatzopoulos and Sebastien Jodogne,
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# ICTEAM UCLouvain, Belgium
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#
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# This program is free software: you can redistribute it and/or
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# modify it under the terms of the GNU Affero General Public License
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# as published by the Free Software Foundation, either version 3 of
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# the License, or (at your option) any later version.
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#
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# This program is distributed in the hope that it will be useful, but
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# WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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# Affero General Public License for more details.
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#
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# You should have received a copy of the GNU Affero General Public License
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# along with this program. If not, see <http://www.gnu.org/licenses/>.
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##
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## Initialize the virtual environment for pytorch.
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## DO NOT add other "import" in this section!
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##
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import sys
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import json
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import orthanc
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config = json.loads(orthanc.GetConfiguration()).get('Mammography', {})
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venv = config.get('VirtualEnv')
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if venv != None:
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# https://orthanc.uclouvain.be/book/plugins/python.html#working-with-virtual-environments
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sys.path.insert(0, venv)
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##
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## Install the Stone Web viewer
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##
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STONE_VERSION = '2024-08-31-StoneWebViewer-DICOM-SR'
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VIEWER_PREFIX = '/mammography-viewer/'
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import os
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SCRIPT_DIR = os.path.dirname(os.path.realpath(__file__))
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VIEWER_DIR = os.path.join(SCRIPT_DIR, 'viewer')
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sys.path.append(os.path.join(SCRIPT_DIR, '..'))
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import download
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os.makedirs(VIEWER_DIR, exist_ok = True)
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download.get(os.path.join(VIEWER_DIR, '%s.zip' % STONE_VERSION),
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'https://github.com/jodogne/orthanc-mammography/raw/master/viewer/%s.zip' % STONE_VERSION,
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4815178, '86b52a17f86e4769d12e9ae680c4a99f')
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import zipfile
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stone_assets = zipfile.ZipFile(os.path.join(VIEWER_DIR, '%s.zip' % STONE_VERSION))
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MIME_TYPES = {
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'.css' : 'text/css',
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'.gif' : 'image/gif',
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'.html' : 'text/html',
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'.jpeg' : 'image/jpeg',
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'.js' : 'text/javascript',
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'.png' : 'image/png',
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}
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def serve_stone_web_viewer(output, uri, **request):
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if not uri.startswith(VIEWER_PREFIX):
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output.SendHttpStatusCode(404)
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elif request['method'] != 'GET':
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output.SendMethodNotAllowed('GET')
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else:
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try:
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path = '%s/%s' % (STONE_VERSION, uri[len(VIEWER_PREFIX):])
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extension = os.path.splitext(path) [1]
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if not extension in MIME_TYPES:
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mime = 'application/octet-stream'
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else:
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mime = MIME_TYPES[extension]
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with stone_assets.open(path) as f:
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output.AnswerBuffer(f.read(), mime)
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except:
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output.SendHttpStatusCode(500)
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orthanc.RegisterRestCallback('%s(.*)' % VIEWER_PREFIX, serve_stone_web_viewer)
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##
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## Load the deep learning model
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##
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import highdicom
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import io
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import os
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import pydicom
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sys.path.append(os.path.join(SCRIPT_DIR, '..'))
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import model
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import dicom_sr
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import dicom_sr_to_pdf
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orthanc.LogWarning('Loading the RetinaNet model for mammography')
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my_retina_net = model.load_retina_net()
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##
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## Install the Orthanc Explorer extension
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##
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with open(os.path.join(SCRIPT_DIR, 'OrthancExplorer.js'), 'r') as f:
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orthanc.ExtendOrthancExplorer(f.read())
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def execute_inference(output, uri, **request):
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if request['method'] != 'POST':
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output.SendMethodNotAllowed('POST')
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else:
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body = json.loads(request['body'])
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f = orthanc.GetDicomForInstance(body['instance'])
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dicom = pydicom.dcmread(io.BytesIO(f))
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if len(dicom.pixel_array.shape) != 2:
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orthanc.LogError('Not a graylevel instance: %s' % body['instance'])
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output.SendHttpStatusCode(400)
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else:
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result = dicom_sr.apply(my_retina_net, dicom, minimum_score=0.2)
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pdf = dicom_sr_to_pdf.create(dicom.pixel_array, result)
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with io.BytesIO() as f:
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pydicom.dcmwrite(f, result)
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f.seek(0)
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content = f.read()
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output.AnswerBuffer(orthanc.RestApiPost('/instances', content), 'application/json')
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with io.BytesIO() as f:
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pydicom.dcmwrite(f, pdf)
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f.seek(0)
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content = f.read()
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output.AnswerBuffer(orthanc.RestApiPost('/instances', content), 'application/json')
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orthanc.RegisterRestCallback('/mammography-apply', execute_inference)
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