Gravity Network for end-to-end small lesion detection
Ciro Russo Alessandro Bria Claudio Marrocco
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.