中圖分類(lèi)號(hào)：TP391.9
文獻(xiàn)標(biāo)志碼：A
DOI: 10.16157/j.issn.0258-7998.223549
中文引用格式： 吳明明，顧春華. 一種乳腺X線影像腫塊的多特征融合檢測(cè)算法[J]. 電子技術(shù)應(yīng)用，2023，49(7)：35-40.
英文引用格式： Wu Mingming，Gu Chunhua. A mutil-feature fusion algorithm for Mammography masses[J]. Application of Electronic Technique，2023，49(7)：35-40.

A mutil-feature fusion algorithm for Mammography masses

Abstract： Aiming at the problem of the high probability of miss and false positive rates in single-view Mammography, an improved automatic detection algorithm is proposed in this paper. The dilated residual network (DRN) combined with a modified feature pyramid network (FPN) is used for the detection of breast masses. The expansion convolution in DRN is used to reduce the number of downsampling of images. The number of layers of the DRN is also increased to satisfy the required input of the FPN. In the FPN structure, the attention mechanism is used to reduce the information loss caused by the direct fusion of different feature maps, while dense connections are used instead of the original lateral connections to make full use of the location and detailed information on the target for the shallow features. Simulation experiments show that the detection accuracy of the designed model on the CBSI-DDSM dataset is improved by 7.1 percent compared to the baseline.

Key words : breast cancer；multi-scale features；object detection；feature pyramid network；dilated residual networks