Laser & Optoelectronics Progress, Volume. 59, Issue 4, 0410003(2022)

Improved Breast Mass Recognition YOLOv3 Algorithm Based on Cross-Layer Feature Aggregation

Shan Wang1, Yiying Hu1、*, Liang Feng2, and Linying Guo2
Author Affiliations
  • 1School of Information Engineering, East China JiaoTong University, Nanchang , Jiangxi 330013, China
  • 2Department of Breast Oncology, The Third Hospital of Nanchang, Nanchang , Jiangxi 330009, China
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    References(23)

    [2] Wang Y, Li J Y, Yang Y L et al. Breast tumor segmentation based on SLIC and GVF snake algorithm[J]. Laser & Optoelectronics Progress, 57, 141023(2020).

    [3] Niu X M, Lü X Q, Gu Y et al. Breast cancer histopathological image classification based on improved ResNeXt[J]. Laser & Optoelectronics Progress, 57, 221021(2020).

    [8] Huang Y J, Shi Z F, Wang Z Q et al. Improved U-net based on mixed loss function for liver medical image segmentation[J]. Laser & Optoelectronics Progress, 57, 221003(2020).

    [9] Sun Y J, Qu Z Y, Li Y H. Study on target detection of breast tumor based on improved mask R-CNN[J]. Acta Optica Sinica, 41, 0212004(2021).

    [22] Guo Y N. Research on lesion detection for mammograms[D](2019).

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    Shan Wang, Yiying Hu, Liang Feng, Linying Guo. Improved Breast Mass Recognition YOLOv3 Algorithm Based on Cross-Layer Feature Aggregation[J]. Laser & Optoelectronics Progress, 2022, 59(4): 0410003

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    Paper Information

    Category: Image Processing

    Received: Feb. 8, 2021

    Accepted: Mar. 22, 2021

    Published Online: Jan. 25, 2022

    The Author Email: Hu Yiying (yiyinghu1125@163.com)

    DOI:10.3788/LOP202259.0410003

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