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Journal of Digital Imaging

, Volume 23, Issue 5, pp 581–591 | Cite as

Novel Computer-Aided Diagnosis Algorithms on Ultrasound Image: Effects on Solid Breast Masses Discrimination

  • Ying Wang
  • Hong Wang
  • Yanhui Guo
  • Chunping Ning
  • Bo Liu
  • H. D. Cheng
  • Jiawei TianEmail author
Article

Abstract

The objective of this study is to retrospectively investigate whether using the newly developed algorithms would improve radiologists’ accuracy for discriminating malignant masses from benign ones on ultrasonographic (US) images. Five radiologists blinded to the histological results and clinical history independently interpreted 226 cases according to the sonographic lexicon of the fourth edition of the Breast Imaging Reporting and Data System and assigned a final assessment category to indicate the probability of malignancy. For each case, each radiologist provided three diagnoses: first with the original images, subsequently with the assistant of the resulting images processed by the proposed CAD algorithms which are called as processed images, and another using the processed images only. Observers’ malignancy rating data were analyzed with the receiver operating characteristic (ROC) curve. For reading only with the processed images, areas under the ROC curve (A z) of each reader (0.863, 0.867, 0.859, 0.868, 0.878) were better than that with the original images (0.772, 0.807, 0.796, 0.828, 0.846), difference of the average A z between the twice reading was significant (p < 0.001). Compared with the results single used processed images, A z of utilizing the combined images were increased (0.866, 0.885, 0.872, 0.894, 0.903), but the difference is not statistically significant (p = 0.081). The proposed CAD method has potential to be a good aid to radiologists in distinguishing malignant breast solid masses from benign ones.

Key words

Computer-aided diagnosis ultrasound breast cancer BI-RADS 

Notes

Acknowledgement

Financial support from the National Natural Science Foundation of China (NSFC) is greatly appreciated; grant numbers: 30670546 and 60873142.

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Copyright information

© Society for Imaging Informatics in Medicine 2009

Authors and Affiliations

  • Ying Wang
    • 1
  • Hong Wang
    • 1
  • Yanhui Guo
    • 2
  • Chunping Ning
    • 1
  • Bo Liu
    • 2
  • H. D. Cheng
    • 2
    • 3
  • Jiawei Tian
    • 1
    Email author
  1. 1.Ultrasound DepartmentThe Second Affiliated Hospital of Harbin Medical UniversityHarbin,People’s Republic of China
  2. 2.School of Computer Science and TechnologyHarbin Institute of TechnologyHarbinChina
  3. 3.Department of Computer ScienceUtah State UniversityLogan,USA

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