When training a U-Net or Mask R-CNN to segment objects, the loss function often uses pixel counts. However, the final output requires conversion to mm² for regulatory submission (FDA, CE marking). If your training data has a variable "pixel value mm²," you must normalize all images to a single spatial resolution before training.
Calculate pixel value in mm².
If your image metadata gives:
import cv2 import numpy as np