Breast　cancer　has　become　the　primary　cancer　endangering　women＇s　life　and　health.　A　large　number　of　evidence　based　on　medicine　show　that　early　screening　can　effectively　reduce　the　mortality　rate　of　breast　cancer.　With　the　development　of　computer　vision　technology,　the　computer-aided　diagnosis　system　for　breast　cancer　screening　and　detection　has　attracted　extensive　attention　from　all　walks　of　life　and　breast　lesion　localization　and　diagnosis　are　the　key　steps.　Therefore,　this　article　starts　from　the　perspective　of　model　feature　construction　to　conduct　an　in-depth　analysis　and　a　comprehensive　summary　of　the　existing　research　on　breast　image　lesion　localization　and　benign-malignant　diagnosis.　This　article　divides　feature　construction　methods　into　three　types　based　on　novel　perspectives:　domain　knowledge-driven,　data-driven,　and　domain　knowledge-driven　fusion　data-driven.　On　this　basis,　the　article　uses　a　systematic　review　method　to　classify,　summarize,　and　compare　the　models　for　breast　image　lesion　localization　and　diagnosis　which　greatly　expands　and　deeply　analyzes　existing　reviews.　In　addition,　this　article　elaborates　on　the　existing　problems　in　current　research　work　and　discusses　the　future　outlook　of　breast　image　lesion　localization　and　benign-malignant　diagnosis.　　©　2024　IEEE.