George-Wu commented on a change in pull request #12331: URL: https://github.com/apache/beam/pull/12331#discussion_r463003111
########## File path: sdks/python/apache_beam/io/gcp/dicomio.py ########## @@ -0,0 +1,419 @@ +# +# Licensed to the Apache Software Foundation (ASF) under one or more +# contributor license agreements. See the NOTICE file distributed with +# this work for additional information regarding copyright ownership. +# The ASF licenses this file to You under the Apache License, Version 2.0 +# (the "License"); you may not use this file except in compliance with +# the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. +# + +"""DICOM io connector +This module implements serval tools to facilitate the interaction between +a Google Cloud Healthcare DICOM store and a beam pipeline. +For more details on DICOM store and API: +https://cloud.google.com/healthcare/docs/how-tos/dicom +DICOM io connector can be used to search metadata or store DICOM files. +When used together with Google Pubsub message connector, a PTransform +implemented in this module can be used to convert pubsub messages to search +requests. Since Traceability is crucial for healthcare API users, every +input or error message will be recorded in the output of the DICOM io +connector. As a result, every PTransform in this module will return a +Pcollection of dict that encodes results and detailed error messages. + +Search instance's metadata (QIDO request) +=================================================== +DicomSearch() wraps the QIDO request client and supports 3 levels of search. +Users should specify the level by setting the 'search_type' entry in the input +dict. They can also refine the search by adding tags to filter the results using +the 'params' entry. Here is a sample usage: + + with Pipeline() as p: + input_dict = p | beam.Create([ + {'project_id': 'abc123', 'type': 'instances',...}, + {'project_id': 'dicom_go', 'type': 'series',...} + ]) + results = input_dict| io.gcp.DicomSearch() + results | 'print successful search' >> beam.Map( + lambda x: print(x['result'] if x['success'] else None)) + results | 'print failed search' >> beam.Map( + lambda x: print(x['result'] if not x['success'] else None)) + +In the example above, successful qido search results and error messages for +failed requests are printed. When used in real life, user can choose to filter +those data and output them to wherever they want. + +Convert DICOM Pubsub message to Qido search request +=================================================== +Healthcare API users might use Beam's Pubsub streaming pipeline to monitor the +store operations (new DICOM file) in a DICOM storage. Pubsub message encodes +DICOM a web store path as well as instance ids. If users are interested in +getting new instance's metadata, they can use PubsubToQido() to convert the +message into Qido Search dict then use DicomSearch(). Here is a sample usage: + + pipeline_options = PipelineOptions() + pipeline_options.view_as(StandardOptions).streaming = True + with beam.Pipeline(options=pipeline_options) as p: + pubsub = p | beam.io.ReadStringFromPubsub(subscription='a_dicom_store') + results = pubsub | PubsubToQido() + success = results | 'filter message' >> beam.Filter(lambda x: x['success']) + qido_dict = success | 'get qido request' >> beam.Map(lambda x: x['result']) + metadata = qido_dict | DicomSearch() + +In the example above, the pipeline is listening to a pubsub topic and waiting +for messages from DICOM API. When a new DICOM file comes into the storage, the +pipeline will receive a pubsub message, convert it to a Qido request dict and +feed it to DicomSearch() PTransform. As a result, users can get the metadata for +every new DICOM file. Note that not every pubsub message received is from DICOM +API, so we to filter the results first. + +Store a DICOM file in a DICOM storage +=================================================== +DicomStoreInstance() wraps store request API and users can use it to send a +DICOM file to a DICOM store. It supports two types of input: 1.file data in +byte[] 2.fileio object. Users should set the 'input_type' when initialzing +this PTransform. Here are the examples: + + with Pipeline() as p: + input_dict = {'project_id': 'abc123', 'type': 'instances',...} + path = "gcs://bucketname/something/a.dcm" + match = p | fileio.MatchFiles(path) + fileio_obj = match | fileio.ReadAll() + results = fileio_obj | DicomStoreInstance(input_dict, 'fileio') + + with Pipeline() as p: + input_dict = {'project_id': 'abc123', 'type': 'instances',...} + f = open("abc.dcm", "rb") + dcm_file = f.read() + byte_file = p | 'create byte file' >> beam.Create([dcm_file]) + results = byte_file | DicomStoreInstance(input_dict, 'bytes') + +The first example uses a PCollection of fileio objects as input. +DicomStoreInstance will read DICOM files from the objects and send them +to a DICOM storage. +The second example uses a PCollection of byte[] as input. DicomStoreInstance +will directly send those DICOM files to a DICOM storage. +Users can also get the operation results in the output PCollection if they want +to handle the failed store requests. +""" + +# pytype: skip-file +from __future__ import absolute_import + +import apache_beam as beam +from apache_beam.io.gcp.dicomclient import DicomApiHttpClient +from apache_beam.transforms import PTransform + + +class DicomSearch(PTransform): + """A PTransform used for retrieving DICOM instance metadata from Google + Cloud DICOM store. It takes a Pcollection of dicts as input and return + a Pcollection of dict as results: + INPUT: + The input dict represents DICOM web path parameters, which has the following + string keys and values: + { + 'project_id': str, + 'region': str, + 'dataset_id': str, + 'dicom_store_id': str, + 'search_type': str, + 'params': dict(str,str) (Optional), + } + Key-value pairs: + project_id: Id of the project in which DICOM store locates. (Required) + region: Region where the DICOM store resides. (Required) + dataset_id: Id of the dataset where DICOM store belongs to. (Required) + dicom_store_id: Id of the dicom store. (Required) + search_type: Which type of search it is, could only be one of the three + values: 'instances', 'series', or 'studies'. (Required) + params: A dict of str:str pairs used to refine QIDO search. (Optional) + Supported tags in three categories: + 1. Studies: + StudyInstanceUID + PatientName + PatientID + AccessionNumber + ReferringPhysicianName + StudyDate + 2. Series: all study level search terms and + SeriesInstanceUID + Modality + 3. Instances: all study/series level search terms and + SOPInstanceUID + e.g. {"StudyInstanceUID":"1","SeriesInstanceUID":"2"} + OUTPUT: + The output dict wraps results as well as error messages: + { + 'result': a list of dicts in JSON style. + 'success': boolean value telling whether the operation is successful. + 'input': detail ids and dicomweb path for this retrieval. + 'status': status code from the server, used as error message. + } + """ + def __init__(self, credential=None): + """Initializes DicomSearch. + Args: + credential: # type: Google credential object, if it is specified, the + Http client will use it to create sessions instead of the default. + """ + self.credential = credential + + def expand(self, pcoll): + return pcoll | beam.ParDo(_QidoSource(self.credential)) + + +class _QidoSource(beam.DoFn): + """A DoFn for executing every qido query request.""" + def __init__(self, credential=None): + self.credential = credential + + def process(self, element): + # Check if all required keys present. + required_keys = [ + 'project_id', 'region', 'dataset_id', 'dicom_store_id', 'search_type' + ] + + error_message = None + + for key in required_keys: + if key not in element: + error_message = 'Must have %s in the dict.' % (key) + break + + if not error_message: + project_id = element['project_id'] + region = element['region'] + dataset_id = element['dataset_id'] + dicom_store_id = element['dicom_store_id'] + search_type = element['search_type'] + params = element['params'] if 'params' in element else None + + # Call qido search http client + if element['search_type'] in ['instances', "studies", "series"]: + result, status_code = DicomApiHttpClient().qido_search( + project_id, region, dataset_id, dicom_store_id, + search_type, params, self.credential + ) + else: + error_message = ( + 'Search type can only be "studies", ' + '"instances" or "series"') Review comment: @pabloem The batch processing is implemented. However I am not sure if my way of setting timestamp is correct, please double check :) ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
