SIFT-DBT: Self-supervised Initialization and Fine-Tuning for Imbalanced Digital Breast Tomosynthesis Image Classification

arXiv:2403.13148v1 Announce Type: cross
Abstract: Digital Breast Tomosynthesis (DBT) is a widely used medical imaging modality for breast cancer screening and diagnosis, offering higher spatial resolution and greater detail through its 3D-like breast volume imaging capability. However, the increased data volume also introduces pronounced data imbalance challenges, where only a small fraction of the volume contains suspicious tissue. This further exacerbates the data imbalance due to the case-level distribution in real-world data and leads to learning a trivial classification model …

abstract arxiv breast cancer screening cancer cancer screening capability challenges classification cs.cv cs.lg data dbt diagnosis digital eess.iv fine-tuning however image imaging medical medical imaging screening sift spatial through type