def finish_series(series_id):
"""
Mark the status of current series as finished(4)
If all the labeled series in current study arenot annotating, then set current study as finished.
:param series_id:
:return:
"""
series_service = SeriesService(get_conn())
series = series_service.query({"series_id": series_id})
if (len(series) > 0):
study_id = series[0]['study_id']
series_service.update({"series_id": series_id},
{"status": SERIES_STATUS.finished.value})
series_in_current_study = series_service.query(
{"study_id": study_id})
all_complete = True
for one_stu in series_in_current_study:
status = one_stu['status']
if status == SERIES_STATUS.annotating.value:
all_complete = False
if all_complete:
study_service = StudiesService(get_conn())
study_service.update({"study_id": study_id},
{'status': STUDY_STATUS.finished.value})
return jsonify({}), 200
def list_studies_info(instance_id):
"""
List all studies basic information.
:param instance_id:
:return:
"""
study_service = StudiesService(get_conn())
studies = study_service.query({'instance_id': instance_id})
return jsonify(studies), 200
def workbench(instance_id, study_id, series_id):
study_service = StudiesService(get_conn())
study_info = study_service.query({"study_id": study_id})
if len(study_info) > 0 and study_info[0]["instance_id"] == int(
instance_id):
study_info = study_info[0]
else:
return render_template("404.html")
label_candidate_service = LabelCandidatesService(get_conn())
label_candidates = label_candidate_service.query(
{"instance_id": instance_id})
series_service = SeriesService(get_conn())
series = series_service.query({
"study_id": study_id,
"series_id": series_id
})
if len(series) > 0 and len(series[0]) > 3:
series = series[0]
series["series_files_list"] = eval(series["series_files_list"])
result = {
"instance_id":
instance_id,
"study_id":
study_id,
"series_id":
series_id,
"study_path":
os.path.join(study_info["folder_name"], ""),
"label_candidates":
label_candidates,
"series_detail":
series,
"dim": [
series['x_dimension'], series['y_dimension'],
series['z_dimension']
]
}
return render_template("workbench.html", data=result)
def add_labels(series_id, file_name):
# Temporary mock the user Id.
user_id = 1
data = request.data
label_service = LabelService(get_conn())
status = label_service.insert(series_id, user_id, file_name, data)
update_status = request.args.get('update_status',
type=bool,
default=False)
if update_status:
series_service = SeriesService(get_conn())
study_service = StudiesService(get_conn())
instance_service = InstanceService(get_conn())
series = series_service.query({'series_id': series_id})
if len(series) > 0:
study_id = series[0]['study_id']
status = series[0]['status']
if status < SERIES_STATUS.annotating.value:
series_service.update(
{'series_id': series_id},
{'status': SERIES_STATUS.annotating.value})
study = study_service.query({'study_id': study_id})
instance_id = study[0]['instance_id']
if study[0]['status'] != STUDY_STATUS.annotating.value:
study_service.update(
{'study_id': study_id},
{'status': STUDY_STATUS.annotating.value})
instance = instance_service.query({'instance_id': instance_id})
if instance[0]['status'] != INSTANCE_STATUS.annotating.value:
instance_service.update(
{'instance_id': instance_id},
{'status': INSTANCE_STATUS.annotating.value})
if status:
return jsonify({}), 201
else:
return jsonify({status: "Transaction Rollback."}), 404
def wireframe_one_study(instance_id, study_id):
t = TicToc()
t.tic()
study_service = StudiesService(get_conn())
study_info = study_service.query({
"instance_id": instance_id,
"study_id": study_id
})
t.toc("study_info", restart=True)
# study_info 0.012129 seconds.
export_service = ExportService(get_conn())
_, _, labels = export_service.save_onestudy_label(
study_id, study_info[0], None, [])
t.toc("labels gen", restart=True)
# labels gen 31.750854 seconds.
crossref_service = CrossRefService()
label_list = crossref_service.accumulate_contours(labels)
t.toc("label_list", restart=True)
# label_list 32.659566 seconds.
result = crossref_service.merge_dicom_orientation(label_list)
t.toc("merge dicom", restart=True)
# merge dicom 8.348602 seconds.
return jsonify(result), 200
def import_dcm(self, instance_id, data_path):
instance_service = InstanceService(self.conn)
instance_service.update({'instance_id': instance_id}, {'status': INSTANCE_STATUS.importing_dicom.value})
series_extraction_service = SeriesExtractionService()
all_series_list = series_extraction_service.extract_series_from_path(os.path.join(DATA_ROOT, data_path))
study_service = StudiesService(self.conn)
series_service = SeriesService(self.conn)
for suid in all_series_list:
series = all_series_list[suid]
patient_uid = 0
study_uid = 0
study_service.insert(instance_id, patient_uid, study_uid, suid, "[]", 0, 0)
study = study_service.query({"instance_id": instance_id, "suid": suid})
study = study[0]
total_files_number = 0
folder_name_arr = []
for series_path in series:
folder_name_arr.append(series_path)
one_series = series[series_path][0]
patient_uid = one_series.info.PatientID
study_uid = one_series.info.StudyID
if patient_uid == "" or study_uid == "":
patient_uid = ""
study_uid = suid
# disp_name = "pid:" + one_series.info.PatientID + "_sid:" + one_series.info.StudyID
total_files_number += one_series.length
series_info = one_series.info
if len(one_series.shape) == 2:
z_dim = 1
x_dim = one_series.shape[0]
y_dim = one_series.shape[1]
else:
z_dim = one_series.shape[0]
x_dim = one_series.shape[1]
y_dim = one_series.shape[2]
series_service.insert(study['study_id'], one_series.description, series_path, one_series.filenames,
one_series.length, series_info.get("WindowWidth"),
series_info.get("WindowCenter"), one_series.sampling[1], one_series.sampling[1],
one_series.sampling[0], x_dim, y_dim, z_dim, series_info.get("PatientID"),
series_info.get("SeriesInstanceUID"), series_info.get("StudyDate") or "", "",
"", SERIES_STATUS.init.value)
study_service.update({"instance_id": instance_id, "suid": suid},
{"total_files_number": total_files_number, "patient_uid": patient_uid,
"study_uid": study_uid, "folder_name": str(folder_name_arr),
"status": STUDY_STATUS.ready_to_annotate.value})
instance_service.update({'instance_id': instance_id}, {'status': INSTANCE_STATUS.ready_to_annotate.value})
return True
def test_list_all_studies(self, client):
res = client.get(url_for('list_all_studies', instance_id=1))
assert res.json == {}
assert res.status == '200 OK'
# Setup studies sample data
ini_service = InitialService()
conn = ini_service.get_connection()
instance_service = InstanceService(conn)
instance_service.insert("Stroke Annotation Task", "CT",
"The stroke CT scans for annotation tasks.",
"tests/services/sample_data", 0, 200, 1, 0)
result = instance_service.query({})
assert result[0]["instance_id"] == 1
assert result[0]["name"] == "Stroke Annotation Task"
studies_service = StudiesService(conn)
studies_service.insert(1, "Dicom_691_2", 25, 0, "folder", 100, 1)
studies_service.insert(1, "Raw_1003/3CH_tagging", 30, 1, "folder", 100,
1)
series_service = SeriesService(conn)
series_service.insert(1, "series1", "series1/path", ["1"], 1, "200",
"200", "0.5", "0.5", "0.5", 512, 512, 512, 1,
100101, "", "", "")
series_service.insert(1, "series2", "series2/path", ["1"], 1, "200",
"200", "0.5", "0.5", "0.5", 512, 512, 512, 1,
100101, "", "", "")
series_service.insert(2, "series3", "series3/path", ["1"], 1, "200",
"200", "0.5", "0.5", "0.5", 512, 512, 512, 1,
100101, "", "", "")
series_service.insert(2, "series4", "series4/path", ["1"], 1, "200",
"200", "0.5", "0.5", "0.5", 512, 512, 512, 1,
100101, "", "", "")
res = client.get(url_for('list_all_studies', instance_id=1))
assert len(res.json[0]) == 2
assert res.json[0][0]["instance_id"] == 1
assert res.json[0][0]["patient_uid"] == "Dicom_691_2"
assert res.json[1][0]["instance_id"] == 1
assert res.json[1][0]["patient_uid"] == "Raw_1003/3CH_tagging"
assert res.status == '200 OK'
def cross_reference(instance_id):
study_service = StudiesService(get_conn())
study_info = study_service.query({"instance_id": instance_id})
return render_template("cmr_reference.html",
studies=study_info,
instance=instance_id)
def save_studies(self,
instance_id,
split_entry_num=100,
start_idx=0,
end_idx=-1,
store_type="train",
save_pair=True,
save_label=True,
save_data=True,
compression=None):
"""
Save all annotations and and dicom data for each study in the instance.
:param instance_id:
:param split_entry_num: create new h5 file if stored entries more than the max split number
:param start_idx: start file number.
:param end_idx: end of the file number.
:param store_type: train or test
:param save_pair: True or False. If save the pair, will only save the series which have labels.
:param save_label: True or False
:param save_data: True or False
:param compression: Whether the hdf5 file compressed or not. "gzip|lzf"
:return:
"""
msg_box = []
instance_service = InstanceService(self.conn)
instance = instance_service.query({"instance_id": instance_id})
instance_name = instance[0]['name']
study_service = StudiesService(self.conn)
studies = study_service.query({"instance_id": instance_id})
study_num = split_entry_num * start_idx
if end_idx == -1:
end_num = len(studies)
else:
end_num = split_entry_num * end_idx
study_h5 = None
time_stamp = str(int(time.time()))
for idx, study in enumerate(studies):
if idx == study_num and idx < end_num:
study_id = study['study_id']
app.logger.info(
f"Save study-instance_id:{instance_id}({instance_name}),study_id:{study_id}"
)
h5_path = os.path.join(OUTPUT_ROOT, str(instance_id))
if study_num % split_entry_num == 0:
if not os.path.exists(h5_path):
os.makedirs(h5_path)
if study_h5 is not None:
study_h5.close()
h5_file_name = f"Export-{instance_id}-{instance_name}-{time_stamp}-{study_num // split_entry_num}.h5"
study_h5 = h5py.File(os.path.join(h5_path, h5_file_name),
'w')
if save_pair:
_, saved_label, _ = self.save_onestudy_label(
study_id, study, study_h5, msg_box, store_type,
compression)
self.save_onestudy_dcm(study_id, study, study_h5, msg_box,
store_type, compression,
saved_label)
else:
if save_label:
self.save_onestudy_label(study_id, study, study_h5,
msg_box, store_type,
compression)
if save_data:
self.save_onestudy_dcm(study_id, study, study_h5,
msg_box, store_type,
compression)
study_num += 1
study_h5.close()
return msg_box