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Gravity Network for end-to-end small lesion detection

Authors :
Russo, Ciro
Bria, Alessandro
Marrocco, Claudio
Publication Year :
2023

Abstract

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.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2309.12876
Document Type :
Working Paper
Full Text :
https://doi.org/10.1016/j.artmed.2024.102842