YOLOV3-BASED BREAST MASS DETECTION METHOD IN MAMMOGRAPHY
Mammography is internationally recognized as an effective screening tool for early breast cancer.This paper proposes a mammographic mass detection method based on YOLOv3 network.The method could complete mass detection of the whole image at a faster speed while ensuring accuracy.By applying transfer learning technology,the mass lesion detection knowledge learned from the digitized mammograms were transferred to the full-field digital mammograms,which effectively solved the current lack of full-field digital mammography datasets.The five-fold cross-validation method was used for evaluation based on DDSM and INbreast datasets.Through extensive experiments,the obtained average accuracy of the mass detection over the five folds is 81.34％.
Deep learningYOLOv3MammographyMass detectionTransfer learning
国家科技期刊平台
NSTL
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