def load(**kwargs):
"""
Load volume data and managed in memory
:param volume: volume data
:param seriesuid: series uid
:return:
"""
try:
volume_path = kwargs['volumepath']
if not os.path.isfile(volume_path):
return response(success=False, message='volume data not exist.')
except Exception as err:
return response(success=False, message=err.message)
try:
vol = cio.read_image(volume_path)
os.remove(volume_path)
size = vol.size().tolist()
imageentity.set_volume(vol)
imageentity.remove_child_entities()
imageentity.add_child_entity(CellEntity(0, False))
imageentity.add_child_entity(CellEntity(1, False))
imageentity.add_child_entity(CellEntity(2, False))
imageentity.init_default_scenes(vol)
log.dev_info("load volume succeed")
return response(content=json.dumps(size),
success=True,
message='load volume succeed')
except Exception as err:
return response(success=False, message=err.message)
def mask_to_contours(mask_fp):
"""
Convert mask to contours
:param mask_fp: Mask file path
:return: Array of contours
"""
log.dev_info('Mask file path: {}'.format(mask_fp))
if not os.path.isfile(mask_fp):
log.dev_error('Path {} is not a mask file')
return None
mask = cio.read_image(mask_fp)
mask.from_numpy(mask.to_numpy(), np.uint8)
size_x, size_y, slice_count = mask.size()
slices = mask.to_numpy()
rst = {}
for index in range(slice_count):
slice = slices[index]
_, thresh = cv2.threshold(slice, 0, 255, cv2.THRESH_BINARY)
_, contours, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
if len(contours) == 0:
continue
graphics = []
for contour in contours:
graphic = []
for cp in contour:
pt = cp[0].tolist()
pt.append(index + 1)
graphic.append(pt)
graphics.append(graphic)
rst[index + 1] = graphics
return rst
def contours_to_mask(mask_fp, contours):
"""
Convert contour to mask(.nii.gz)
:param contours: dictionary of contours
:param size: mask shape
:return: mask file path
"""
mask = cio.read_image(mask_fp)
size_x, size_y, slice_count = mask.size()
mask.from_numpy(np.zeros(np.array([slice_count, size_y, size_x])), np.uint8)
slices = mask.to_numpy()
for index in contours:
slice = slices[int(index) - 1]
graphics = contours[index]
for pts in graphics:
num_pts = len(pts)
for i in range(num_pts):
pt = pts[i]
prev = pts[num_pts - 1] if i == 0 else pts[i - 1]
rr, cc, _ = line_aa(prev[1], prev[0], pt[1], pt[0])
rr[rr >= size_y] = size_y - 1
cc[cc >= size_x] = size_x - 1
slice[rr, cc] = 1
slices[int(index) - 1] = binary_fill_holes(slice).astype(np.uint8)
mask.from_numpy(slices, np.uint8)
cio.write_image(mask, mask_fp)
def seg(self, series_uid):
try:
series, msg = series_ctx.retrieve(series_uid=series_uid)
if len(series) == 0:
return False, 'series_uid is wrong'
mask_fp = file_path_ferry.volumePath + r'{}_mask.nii.gz'.format(series_uid)
if os.path.isfile(mask_fp):
os.remove(mask_fp)
volume_path = series[0].seriespixeldatafilepath
im = read_image(volume_path)
model = autoseg_load_model(r'D:\segmentation_model\VSEG_Heart_20180611_01', 0)
seg = autoseg_volume(im, model)
write_image(seg, mask_fp)
return mask_fp, None
except Exception as ex:
return False, ex.message
def load_volume(self, volume_path, series_uid):
"""
Load volume data to memory
:param volume: volumn data
:param series_uid: series uid
:return: True or False
"""
if volume_path is None:
return False, 'Volume data is None.'
im = read_image(volume_path)
# manage volume data in a dictionary
self.volumes[series_uid] = im
# init config info of this volume
self.configs[series_uid] = {}
self.configs[series_uid]['size'] = [512, 512, 57]
self.configs[series_uid]['center'] = im.center()
self.configs[series_uid]['cursor'] = im.center()
self.configs[series_uid]['spacing'] = im.spacing() # [1, 1, 1]
self.configs[series_uid]['zoom_factor'] = 1
self.configs[series_uid]['win_center'] = 0
self.configs[series_uid]['win_width'] = 2000
self.configs[series_uid]['colormode'] = 0
self.configs[series_uid]['alpha'] = 1
self.configs[series_uid]['default_v'] = -1024
self.configs[series_uid]['transverse_axis'] = [[1, 0, 0], [0, 1, 0],
[0, 0, 1]]
self.configs[series_uid]['saggital_axis'] = [[0, 1, 0], [0, 0, -1],
[1, 0, 0]]
self.configs[series_uid]['coronal_axis'] = [[1, 0, 0], [0, 0, -1],
[0, 1, 0]]
# switch current volume to this volume
self.change_volume(series_uid)
self.look_at['transverse'] = im.center()
self.look_at['coronal'] = im.center()
self.look_at['saggital'] = im.center()
return True, 'Load succeed.'