论文标题
CircLenet：无锚检测带有圆形表示
CircleNet: Anchor-free Detection with Circle Representation
论文作者
论文摘要
对象检测网络在计算机视觉中具有强大的功能，但不一定针对生物医学对象检测进行了优化。在这项工作中，我们提出了CircLenet，这是一种简单的无锚检测方法，具有圆形表示，用于检测球形肾小球。与基于传统边界框的检测方法不同，边界圆（1）降低了检测自由度的程度，（2）是自然旋转不变的，（3），并针对球形对象进行了优化。启用此表示形式的关键创新是带有圆形检测头的无锚框架。我们在检测肾小球的背景下评估了圆圈。圆环将肾小球检测的平均精度从0.598提高到0.647。另一个关键优势是，与边界框表示相比，CircLenet可以实现更好的旋转一致性。
Object detection networks are powerful in computer vision, but not necessarily optimized for biomedical object detection. In this work, we propose CircleNet, a simple anchor-free detection method with circle representation for detection of the ball-shaped glomerulus. Different from the traditional bounding box based detection method, the bounding circle (1) reduces the degrees of freedom of detection representation, (2) is naturally rotation invariant, (3) and optimized for ball-shaped objects. The key innovation to enable this representation is the anchor-free framework with the circle detection head. We evaluate CircleNet in the context of detection of glomerulus. CircleNet increases average precision of the glomerulus detection from 0.598 to 0.647. Another key advantage is that CircleNet achieves better rotation consistency compared with bounding box representations.
