Breast mass detection and diagnosis using fused features with density.

Journal: Journal of X-ray science and technology
Published Date: Jan 1, 2019

Abstract

BACKGROUND: The morbidity of breast cancer has been increased in these years and ranked the first of all female diseases. Computer-aided diagnosis techniques for mammograms can help radiologists find early breast lesions. In mammograms, the degree of malignancy of the tumor is not only related to its morphology and texture features, but also closely related to the density of the tumor. However, in the current research on breast masses detection and diagnosis, people usually use the fusion feature of morphology and texture but neglect density, or only the density feature is considered. Therefore, this paper proposes a method to detect and diagnose the breast mass using fused features with density.

Authors

  • Zhiqiong Wang
    Sino-Dutch Biomedical & Information Engineering School, Northeastern University, China.
  • Yukun Huang
    College of Information Science and Engineering, Northeastern University, China.
  • Mo Li
    School of Computer Science and Engineering, Key Laboratory of Big Data Management and Analytics (Liaoning), Northeastern University, China.
  • Hao Zhang
    College of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou, 450002, China.
  • Chen Li
    School of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, China.
  • Junchang Xin
    School of Computer Science & Engineering, Northeastern University, China. Electronic address: xinjunchang@cse.neu.edu.cn.
  • Wei Qian
    Department of Electrical and Computer Engineering, University of Texas at El Paso, 500 West University Avenue, El Paso, TX 79968, USA; Sino-Dutch Biomedical and Information Engineering School, Northeastern University, No.11, Lane 3, Wenhua Road, Heping District, Shenyang, Liaoning 110819, China. Electronic address: wqian@utep.edu.

Keywords

External Resources

Popular Topics
Recent Journals