SimpleITK 获取二值图像bbox

sitk_ seg_ img = sitk . ReadImage( m )
bbox =get_ bbox_ from mask(sitk_ seg_ _img)

def get_bbox_from_mask(bin_mask):
    # One is : sitk.LabelShapeStatisticsImageFilter()
    #          Input: bin_mask
    #          Output: bbox<x,y,z, length, width, height>
    #                  here, x y z --> (R, A, S) when direction=(1,1,1)
    #          Note: for GetArrayFromImage , it is <z, y, x>
    # Front idx = 1, background idx = 0
    label_filter = sitk.LabelShapeStatisticsImageFilter()
    label_filter.Execute(bin_mask)
    bbox = label_filter.GetBoundingBox(1)
    return bbox


def get_bbox_from_volme_and_mask(sitk_seg_img):
    # Another is : sitk.LabelStatisticsImageFilter()
    #          Input: <raw_img ,bin_mask>
    #          Output: bbox = <x_min, x_max, y_min, y_max, z_min, z_max>
    #          Note: for GetArrayFromImage , it is <z, y, x>
    # Front idx = 1, background idx = 0
    label_filter = sitk.LabelStatisticsImageFilter()
    label_filter.Execute(sitk_seg_img, sitk_seg_img)
    bbox = label_filter.GetBoundingBox(1)
    return bbox

 def get_bbox_from_mask(self, bin_mask):
    # One is : sitk.LabelShapeStatisticsImageFilter()
    #          Input: bin_mask
    #          Output: bbox<x,y,z, length, width, height>
    #                  here, x y z --> (R, A, S) when direction=(1,1,1)
    #          Note: for GetArrayFromImage , it is <z, y, x>
    # Front idx = 1, background idx = 0
    label_filter = sitk.LabelShapeStatisticsImageFilter()
    label_filter.Execute(bin_mask)
    bbox = label_filter.GetBoundingBox(1)
    return bbox

  def landmarkCanal(self):
    canalBoneNode = slicer.util.getFirstNodeByClassByName("vtkMRMLLabelMapVolumeNode", self._canal_seg)
    segbounds = np.zeros([6])
    canalBoneNode.GetBounds(segbounds)
    print("segbounds \n", segbounds)
    itkImagelabel = sitkUtils.PullVolumeFromSlicer(canalBoneNode)
    itkImagelabel = sitk.Cast(itkImagelabel, sitk.sitkUInt8)
    bbox = self.get_bbox_from_mask(itkImagelabel)
    print("bbox: \n", bbox)