赵柳, 颜光前, 吴俊, 罗华友, 孙亮, 舒若. 基于ABUS冠状面图像的乳头位置自动检测算法[J]. 云南大学学报(自然科学版), 2019, 41(3): 464-469. doi: 10.7540/j.ynu.20180318
引用本文: 赵柳, 颜光前, 吴俊, 罗华友, 孙亮, 舒若. 基于ABUS冠状面图像的乳头位置自动检测算法[J]. 云南大学学报(自然科学版), 2019, 41(3): 464-469. doi: 10.7540/j.ynu.20180318
ZHAO Liu, YAN Guang-qian, WU Jun, LUO Hua-you, SUN Liang, SHU Ruo. An automatic algorithm for the nipple location detection based on ABUS coronal images[J]. Journal of Yunnan University: Natural Sciences Edition, 2019, 41(3): 464-469. DOI: 10.7540/j.ynu.20180318
Citation: ZHAO Liu, YAN Guang-qian, WU Jun, LUO Hua-you, SUN Liang, SHU Ruo. An automatic algorithm for the nipple location detection based on ABUS coronal images[J]. Journal of Yunnan University: Natural Sciences Edition, 2019, 41(3): 464-469. DOI: 10.7540/j.ynu.20180318

基于ABUS冠状面图像的乳头位置自动检测算法

An automatic algorithm for the nipple location detection based on ABUS coronal images

  • 摘要: 乳腺疾病发生在以乳头为中心划分的区域中,乳头的准确定位对乳腺疾病的诊断具有重要的临床意义. 提出一种基于自动化三维乳腺超声(ABUS)冠状面图像的乳头位置自动检测算法. 首先采用图像掩模提取感兴趣区域(ROI);然后对ROI进行图像预处理操作以提高目标区域识别的精确度和运算效率;最后通过霍夫变换圆检测和排除误判圆操作获得乳头的圆心坐标和半径. 结果表明:本算法能有效检测到乳头位置,且检测准确率可达94.7%.

     

    Abstract: Breast disease occurs in the divided area with the nipple as the center. Accurate positioning of the nipple has important clinical value for the diagnosis of breast disease. In this paper, an algorithm for the nipple location automatic detection is proposed based on automated 3D breast ultrasound (ABUS) coronal images. Firstly, a mask is applied to find the region of interest (ROI). Then, the image pre-processing operations are used to improve the accuracy and efficiency of the target area identification. Finally, central coordinate and radius of the nipple are obtained by using the circle Hough transform and the exclusion of misjudgment circles. It is shown in the results that the proposed algorithm can effectively detect the location of the nipple, and the detection accuracy can achieve 94.7%.

     

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