def test_parse_dicom_file():
link_df = load_pid_oid()
pid = link_df['patient_id'][0]
fid = 59
dicom_parser = parsers.DicomParser(pid, fid)
dicom_image = dicom_parser.parse()
assert dicom_image.shape == (256, 256, 3)
fid = -30
dicom_parser = parsers.DicomParser(pid, fid)
dicom_image = dicom_parser.parse()
assert dicom_image is None
def test_parse_boolean_mask():
link_df = load_pid_oid()
pid = link_df['patient_id'][0]
oid = link_df['original_id'][0]
fid = 59
dicom_parser = parsers.DicomParser(pid, fid)
dicom_image = dicom_parser.parse()
icontour_type = 'i'
icontour_parser = parsers.ContourParser(oid, fid, icontour_type)
icontour_polygon = icontour_parser.parse()
imask_parser = parsers.MaskParser(dicom_image, icontour_polygon)
imask = imask_parser.parse()
assert imask.shape == dicom_image.shape
ocontour_type = 'o'
ocontour_parser = parsers.ContourParser(oid, fid, ocontour_type)
ocontour_polygon = ocontour_parser.parse()
omask_parser = parsers.MaskParser(dicom_image, ocontour_polygon)
omask = omask_parser.parse()
assert omask.shape == dicom_image.shape
mask_parser = parsers.MaskParser(None, icontour_polygon)
mask = mask_parser.parse()
assert mask is None
mask_parser = parsers.MaskParser(dicom_image, None)
mask = mask_parser.parse()
assert mask is None
def test_visualize_dicom_image():
link_df = load_pid_oid()
pid = link_df['patient_id'][0]
fid = 59
dicom_parser = parsers.DicomParser(pid, fid)
dicom_parser.visualize()
def test__construct_dicom_filename():
link_df = load_pid_oid()
pid = link_df['patient_id'][0]
fid = 59
expected_fn = 'dicoms/' + pid + '/' + str(fid) + '.dcm'
dicom_parser = parsers.DicomParser(pid, fid)
dicom_fn = dicom_parser._construct_filename()
assert dicom_fn == expected_fn
fid = -123
dicom_parser = parsers.DicomParser(pid, fid)
try:
dicom_fn = dicom_parser._construct_filename()
except IOError:
print('passed detecting non-existing dicom file.')
def test__plot_input_output():
link_fn = 'link.csv'
link_df = pd.read_csv(link_fn)
pid = link_df['patient_id'][0]
oid = link_df['original_id'][0]
fid = 59
dicom_parser = parsers.DicomParser(pid, fid)
dicom_image = dicom_parser.parse()
icontour_type = 'i'
icontour_parser = parsers.ContourParser(oid, fid, icontour_type)
icontour_polygon = icontour_parser.parse()
imask_parser = parsers.MaskParser(dicom_image, icontour_polygon)
imask = imask_parser.parse()
ocontour_type = 'o'
ocontour_parser = parsers.ContourParser(oid, fid, ocontour_type)
ocontour_polygon = ocontour_parser.parse()
omask_parser = parsers.MaskParser(dicom_image, ocontour_polygon)
omask = omask_parser.parse()
train_pipe = pipeline.TrainingPipeline(link_fn, 8)
train_pipe._plot_input_output(dicom_image, imask, omask)
def test__process_dicom_image():
link_df = load_pid_oid()
pid = link_df['patient_id'][0]
fid = 59
dicom_parser = parsers.DicomParser(pid, fid)
fake_dicom_image = np.random.randint(0, 1000, size=[256, 256])
dicom_rgb = dicom_parser._process_dicom_image(fake_dicom_image)
assert dicom_rgb.min() >= 0
assert dicom_rgb.max() <= 255
assert dicom_rgb.shape == (256, 256, 3)
def test_visualize_boolean_mask():
link_df = load_pid_oid()
pid = link_df['patient_id'][0]
fid = 59
dicom_parser = parsers.DicomParser(pid, fid)
dicom_image = dicom_parser.parse()
oid = link_df['original_id'][0]
icontour_type = 'i'
icontour_parser = parsers.ContourParser(oid, fid, icontour_type)
icontour_polygon = icontour_parser.parse()
imask_parser = parsers.MaskParser(dicom_image, icontour_polygon)
imask_parser.visualize()
ocontour_type = 'o'
ocontour_parser = parsers.ContourParser(oid, fid, ocontour_type)
ocontour_polygon = ocontour_parser.parse()
omask_parser = parsers.MaskParser(dicom_image, ocontour_polygon)
omask_parser.visualize()
def _parse_input_output(self, pid_oid, visualize):
"""Parse all the paired up DICOM, contour, and producing bool masks.
Params:
pid_oid: DataFrame stores: `patient_id`, `original_id`,
list of `file_id`
visualize: boolean - if True, invoke data visualization
"""
dicom_input = []
mask_output = []
for _, row in pid_oid.iterrows():
pid = row['patient_id']
oid = row['original_id']
fids = row['file_id']
for fid in fids:
dicom = parsers.DicomParser(pid, fid).parse()
masks = []
for contour_type in self._contour_types:
contour = parsers.ContourParser(oid, fid,
contour_type).parse()
if dicom is not None and contour is not None:
mask = parsers.MaskParser(dicom, contour).parse()
masks.append(mask)
if len(masks) == 2:
dicom_input.append(dicom)
mask_output.append(np.stack(masks, -1))
if visualize and dicom is not None and len(masks) == 2:
self._plot_input_output(dicom, masks[0], masks[1])
self._inputs = np.stack(dicom_input, axis=0)
self._targets = np.stack(mask_output, axis=0)