  Cerebral hematoma grows rapidly in 6-24 hours and misprediction of the growth
can be fatal if it is not operated by a brain surgeon. There are two types of
cerebral hematomas: one that grows rapidly and the other that does not grow
rapidly. We are developing the technique of artificial intelligence to
determine whether the CT image includes the cerebral hematoma which leads to
the rapid growth. This problem has various difficulties: the few positive cases
in this classification problem of cerebral hematoma and the targeted hematoma
has deformable object. Other difficulties include the imbalance classification,
the covariate shift, the small data, and the spurious correlation problems. It
is difficult with the plain CNN classification such as VGG. This paper proposes
the joint learning of semantic segmentation and classification and evaluate the
performance of this.
