4.6 Article

Classification of Benign and Malignant Breast Tumors Using H-Scan Ultrasound Imaging

Journal

DIAGNOSTICS
Volume 9, Issue 4, Pages -

Publisher

MDPI
DOI: 10.3390/diagnostics9040182

Keywords

breast cancer; H-scan ultrasound imaging; Hermite polynomial; scatterer size; ultrasound tissue characterization

Funding

  1. Beijing Natural Science Foundation [4184081]
  2. National Natural Science Foundation of China [11804013, 61871005, 71661167001, 61801312]
  3. International Research Cooperation Seed Fund of Beijing University of Technology [2018A15]
  4. Beijing University of Technology
  5. Intelligent Physiological Measurement and Clinical Translation, Beijing International Base for Scientific and Technological Cooperation

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Breast cancer is one of the most common cancers among women worldwide. Ultrasound imaging has been widely used in the detection and diagnosis of breast tumors. However, due to factors such as limited spatial resolution and speckle noise, classification of benign and malignant breast tumors using conventional B-mode ultrasound still remains a challenging task. H-scan is a new ultrasound technique that images the relative size of acoustic scatterers. However, the feasibility of H-scan ultrasound imaging in the classification of benign and malignant breast tumors has not been investigated. In this paper, we proposed a new method based on H-scan ultrasound imaging to classify benign and malignant breast tumors. Backscattered ultrasound radiofrequency signals of 100 breast tumors were used (48 benign and 52 malignant cases). H-scan ultrasound images were constructed with the radiofrequency signals by matched filtering using Gaussian-weighted Hermite polynomials. Experimental results showed that benign breast tumors had more red components, while malignant breast tumors had more blue components in H-scan ultrasound images. There were significant differences between the RGB channels of H-scan ultrasound images of benign and malignant breast tumors. We conclude H-scan ultrasound imaging can be used as a new method for classifying benign and malignant breast tumors.

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