1 sitk_ seg_ img = sitk . ReadImage( m )
2 bbox =get_ bbox_ from mask(sitk_ seg_ _img)
3
4 def get_bbox_from_mask(bin_mask):
5 # One is : sitk.LabelShapeStatisticsImageFilter()
6 # Input: bin_mask
7 # Output: bbox<x,y,z, length, width, height>
8 # here, x y z --> (R, A, S) when direction=(1,1,1)
9 # Note: for GetArrayFromImage , it is <z, y, x>
10 # Front idx = 1, background idx = 0
11 label_filter = sitk.LabelShapeStatisticsImageFilter()
12 label_filter.Execute(bin_mask)
13 bbox = label_filter.GetBoundingBox(1)
14 return bbox
15
16
17 def get_bbox_from_volme_and_mask(sitk_seg_img):
18 # Another is : sitk.LabelStatisticsImageFilter()
19 # Input: <raw_img ,bin_mask>
20 # Output: bbox = <x_min, x_max, y_min, y_max, z_min, z_max>
21 # Note: for GetArrayFromImage , it is <z, y, x>
22 # Front idx = 1, background idx = 0
23 label_filter = sitk.LabelStatisticsImageFilter()
24 label_filter.Execute(sitk_seg_img, sitk_seg_img)
25 bbox = label_filter.GetBoundingBox(1)
26 return bbox
1 def get_bbox_from_mask(self, bin_mask):
2 # One is : sitk.LabelShapeStatisticsImageFilter()
3 # Input: bin_mask
4 # Output: bbox<x,y,z, length, width, height>
5 # here, x y z --> (R, A, S) when direction=(1,1,1)
6 # Note: for GetArrayFromImage , it is <z, y, x>
7 # Front idx = 1, background idx = 0
8 label_filter = sitk.LabelShapeStatisticsImageFilter()
9 label_filter.Execute(bin_mask)
10 bbox = label_filter.GetBoundingBox(1)
11 return bbox
12
13 def landmarkCanal(self):
14 canalBoneNode = slicer.util.getFirstNodeByClassByName("vtkMRMLLabelMapVolumeNode", self._canal_seg)
15 segbounds = np.zeros([6])
16 canalBoneNode.GetBounds(segbounds)
17 print("segbounds \n", segbounds)
18 itkImagelabel = sitkUtils.PullVolumeFromSlicer(canalBoneNode)
19 itkImagelabel = sitk.Cast(itkImagelabel, sitk.sitkUInt8)
20 bbox = self.get_bbox_from_mask(itkImagelabel)
21 print("bbox: \n", bbox)
