Abstract
Breast microcalcification is one of the important imaging features of early breast cancer and the key to early diagnosis of breast cancer. Ultrasound imaging has the advantages of non-radiation, good real-time performance and low cost. It is widely used in the detection of breast diseases. However, due to factors such as limited spatial resolution and speckle noise, it is difficult to detect breast microcalcification through traditional B-mode ultrasound. On the basis of summarizing the characteristics of breast microcalcification and the limitations of traditional ultrasound imaging, this paper reviewed the research advance of ultrasound detection methods for breast microcalcification in recent years. These methods included high-frequency ultrasound, B-ultrasound image post-processing, ultrasound elastography, time reversal with multiple signal classification, high-frequency spatial information, second-order ultrasound field imaging, and photoacoustic imaging. The related principles of these methods were introduced. At the same time, the characteristics and limitations of various methods were discussed and analyzed deeply. The ultrasonic detection methods for breast microcalcification were summarized, and the future development was proposed. The methods have improved the performance of traditional B-mode ultrasound in detecting microcalcification to some extent, however, there is still a gap compared with mammography. The future development trend of the breast microcalcification ultrasound detection technology includes fusion of detection techniques, comparison and evaluation of detection methods, and diagnosis and classification of lesion types.
| Translated title of the contribution | Review of Ultrasound Detection Methods for Breast Microcalcification |
|---|---|
| Original language | Chinese (Traditional) |
| Pages (from-to) | 217-226 |
| Number of pages | 10 |
| Journal | Beijing Gongye Daxue Xuebao/Journal of Beijing University of Technology |
| Volume | 46 |
| Issue number | 2 |
| DOIs | |
| State | Published - 01 02 2020 |
Bibliographical note
Publisher Copyright:© 2020, Editorial Department of Journal of Beijing University of Technology. All right reserved.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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