  Box representation has been extensively used for object detection in computer
vision. Such representation is efficacious but not necessarily optimized for
biomedical objects (e.g., glomeruli), which play an essential role in renal
pathology. In this paper, we propose a simple circle representation for medical
object detection and introduce CircleNet, an anchor-free detection framework.
Compared with the conventional bounding box representation, the proposed
bounding circle representation innovates in three-fold: (1) it is optimized for
ball-shaped biomedical objects; (2) The circle representation reduced the
degree of freedom compared with box representation; (3) It is naturally more
rotation invariant. When detecting glomeruli and nuclei on pathological images,
the proposed circle representation achieved superior detection performance and
be more rotation-invariant, compared with the bounding box. The code has been
made publicly available: https://github.com/hrlblab/CircleNet
