  Lesions are injuries and abnormal tissues in the human body. Detecting
lesions in 3D Computed Tomography (CT) scans can be time-consuming even for
very experienced physicians and radiologists. In recent years, CNN based lesion
detectors have demonstrated huge potentials. Most of current state-of-the-art
lesion detectors employ anchors to enumerate all possible bounding boxes with
respect to the dataset in process. This anchor mechanism greatly improves the
detection performance while also constraining the generalization ability of
detectors. In this paper, we propose an anchor-free lesion detector. The anchor
mechanism is removed and lesions are formalized as single keypoints. By doing
so, we witness a considerable performance gain in terms of both accuracy and
inference speed compared with the anchor-based baseline
