  The PD-L1 rate, the number of PD-L1 positive tumor cells over the total
number of all tumor cells, is an important metric for immunotherapy. This
metric is recorded as diagnostic information with pathological images. In this
paper, we propose a proportion estimation method with a small amount of
cell-level annotation and proportion annotation, which can be easily collected.
Since the PD-L1 rate is calculated from only `tumor cells' and not using
`non-tumor cells', we first detect tumor cells with a detection model. Then, we
estimate the PD-L1 proportion by introducing a masking technique to `learning
from label proportion.' In addition, we propose a weighted focal proportion
loss to address data imbalance problems. Experiments using clinical data
demonstrate the effectiveness of our method. Our method achieved the best
performance in comparisons.
