This paper introduces a novel one-stage end-to-end detector specifically designed to detect small lesions in medical images. Precise localization of small lesions presents challenges due to their appearance and the diverse contextual backgrounds in which they are found. To address this, our approach introduces a new type of pixel-based anchor that dynamically moves towards the targeted lesion for detection. We refer to this new architecture as GravityNet, and the novel anchors as gravity points since they appear to be "attracted" by the lesions. We conducted experiments on two well-established medical problems involving small lesions to evaluate the performance of the proposed approach: microcalcifications detection in digital mammograms and microaneurysms detection in digital fundus images. Our method demonstrates promising results in effectively detecting small lesions in these medical imaging tasks.

本文介绍了一种新颖的一阶段端到端检测器，专门设计用于检测医学图像中的小病变。通过引入一种新类型的基于像素的锚点，该方法解决了小病变定位的挑战，并在数字乳房X线摄影和数字底片图像中进行了实验证明了该方法在有效检测这些医学图像任务中的小病变方面具有良好的结果。

用于端到端小病变检测的重力网络