code: def mask_from_blur(
      x: Tensor, window, sigma=0.3, thresh=0.05, remove_max=True
  ):
      "Create a mask from the blurred image"
      p = x.windowed(*window)
      if remove_max:
          p[p == 1] = 0
      return gauss_blur2d(p, s=sigma * x.shape[-1]) > thresh
  
imports: from __future__ import annotations
  from ..basics import *
  from ..vision.all import *
  from ..data.transforms import *
  import pydicom, kornia, skimage
  from pydicom.dataset import Dataset
  from pydicom.tag import BaseTag
  from pydicom.multival import MultiValue
  from PIL import Image
label_desc: Use image node_id 18 for calling a global function with example usage: mask_from_blur(x, window, sigma, thresh, remove_max) and returns: unknown