The H-scan for Identification of Scatterers

The H-scan is based on a simplified framework for characterizing scattering behavior, and visualizing the results as color-coding of the B-scan image. The methodology begins with a standard convolution model of pulse-echo formation from typical situations, and then matches those results to the mathematics of Gaussian Weighted Hermite Functions. In this framework, echoes can be classified as returning from specific categories of scatterers, and these can be conveniently displayed as colors. Thus, some information not evident in conventional grayscale pulse-echo images can be visualized in the H-scan format. Learn more about the H-scan at the links below and the journal articles following.

Journal Articles

  1. Development of a multiparametric ultrasound image using an integrated system and method to assess hepatic steatosis
    L. Basavarajappa, M. Khairalseed, K. J. Parker, and K. Hoyt
    Proceedings, IEEE South Asian Ultrasonics Symposium, doi: 10.1109/SAUS61785.2024.10563849 , pp. 1 -4  (2024). View PDF
  2. Multiparametrics quantification and visualization of liver fat using ultrasound
    J. Baek, A. El Kaffas, A. Kamaya, K. Hoyt, and K. J. Parker
    WFUMB Ultrasound Open, vol. 1, no. 1 , pp. 100045-1 -100045-9  (2024). View PDF
  3. H-scan discrimination for tumor microenvironmental heterogeneity in melanoma
    J. Baek, S. S. Qin, P. A. Prieto, and K. J. Parker
    Ultrasound Med Biol, vol. 50, no. 2 , pp. 268 -276  (2024). View PDF
  4. Multiparametric ultrasound imaging for early-stage steatosis: comparison with magnetic resonance imaging-based proton density fat fraction
    J. Baek, L. Basavarajappa, R. Margolis, L, Arthur, J. Li, K. Hoyt, and K. J. Parker
    Med Phys, vol. 51, no. 2 , pp. 1313 -1325  (2023). View PDF
  5. Detecting kidney fibrosis using H-scan
    J. Baek, E. Hysi, X. He, D. A. Yuen, M. C. Kolios, and K. J. Parker
    Proceedings, 2022 IEEE International Ultrasonics Symposium, doi: 10.1109/IUS54386.2022.9957217 , pp. 1 -4  (2022). View PDF
  6. Breast lesion detection and visualization utilizing artificial intelligence and the H-scan
    J. Baek, A. M. O'Connell, and K. J. Parker
    Proceedings, 2022 IEEE International Ultrasonics Symposium, doi: 10.1109/IUS54386.2022.9957217 , pp. 1 -4  (2022). View PDF
  7. Improving breast cancer diagnosis by incorporating raw ultrasound parameters into machine learning
    J. Baek, A. M. O'Connell, and K. J. Parker
    Mach Learn Sci Technol, vol. 3, no. 4 , pp. 045013-1 -045013-19  (2022). View PDF
  8. Disease-specific imaging utilizing support vector machine classification of H-scan parameters- assessment of steatosis in a rat model
    J. Baek, L. Basavarajappa, K. Hoyt, and K. J. Parker
    IEEE Trans Ultrason Ferroelectr Freq Control, vol. 69, no. 2 , pp. 720 -731  (2022). View PDF
  9. H-scan imaging and quantitative measurement to distinguish melanoma metastasis
    J. Baek, S. S. Qin, P. A. Prieto, and K. J. Parker
    Proceedings, 2021 IEEE International Ultrasonics Symposium, DOI: 10.1109/IUS52206.2021.9593760 , pp. 1 -4  (2021). View PDF
  10. Early detection of liver steatosis using multiparametric ultrasound imaging
    L. Basavarajappa, J. Li, H. Tai, J. Song, K. J. Parker, and K. Hoyt
    Proceedings, 2021 IEEE International Ultrasonics Symposium, DOI: 10.1109/IUS52206.2021.9593500 , pp. 1 -4  (2021). View PDF
  11. Disease-specific imaging with H-scan trajectories and support vector machine to visualize the progression of liver diseases
    J. Baek and K. J. Parker
    Proceedings, 2021 IEEE International Ultrasonics Symposium, DOI: 10.1109/IUS52206.2021.9593627 , pp. 1 -4  (2021). View PDF
  12. H-scan trajectories indicate the progression of specific diseases
    J. Baek and K. J. Parker
    Med Phys, vol. 48, no. 9 , pp. 5047 -5058  (2021). View PDF
  13. Clusters of ultrasound scattering parameters for the classification of steatotic and normal livers
    J. Baek, S. S. Poul, L. Basavarajappa, S. Reddy, H. Tai, K. Hoyt, and K. J. Parker
    Ultrasound Med Biol, vol. 47, no. 10 , pp. 3014 -3017  (2021). View PDF
  14. Multiparametric ultrasound imaging for the assessment of normal versus steatotic livers
    L. Basavarajappa, J. Baek, S. Reddy, J. Song, H. Tai, G. Rijal, K. J. Parker, and K. Hoyt
    Nature Scientific Reports, vol. 11, no. 1 , pp. 2655-1 -2655-11  (2021). View PDF
  15. Scattering signatures of normal versus abnormal livers with support vector machine classification
    J. Baek, S. S. Poul, T. A. Swanson, T. A. Tuthill, and K. J. Parker
    Ultrasound Med Bio, vol. 46, no. 12 , pp. 3379 -3392  (2020). View PDF
  16. H-scan, shear wave and bioluminescent assessment of the progression of pancreatic cancer metastases in the liver
    J. Baek, R. Ahmed, J. Ye, S. A. Gerber, K. J. Parker, and M. M. Doyley
    Ultrasound Med Biol, vol. 46, no. 12 , pp. 3369 -3378  (2020). View PDF
  17. Early assessment of nonalcoholic fatty liver disease using multiparametric ultrasound imaging
    L. Basavarajappa, S. Reddy, H. Tai, J. Song, G. Rijal, K. J. Parker, and K. Hoyt
    Proceedings, IEEE Ultrasonics Symposium (IUS) , pp. 1 -4  (2020). View PDF
  18. Support vector machine (SVM) based liver classification: fibrosis, steatosis, and inflammation
    J. Baek, T. A. Swanson, T. A. Tuthill, and K. J. Parker
    Proceedings, IEEE Ultrasonics Symposium (IUS) , pp. 1 -4  (2020). View PDF
  19. Fine-tuning the H-scan for discriminating changes in tissue scatterers
    K. J. Parker and J. Baek
    Biomed Phys Eng Express, vol. 6, no. 4 , pp. 045012-1 -045012-15  (2020). View PDF
  20. Monitoring early breast cancer response to neoadjuvant therapy using H-scan ultrasound imaging: preliminary preclinical results
    M. Khairalseed, K. Javed, G. Jashkaran, J. W. Kim, K. J. Parker, and K. Hoyt
    J Ultrasound Med, vol. 38, no. 5 , pp. 1259 -1268  (2019). View PDF
  21. Real-time H-scan ultrasound imaging using a Verasonics research scanner
    M. Khairalseed, K. Brown, K. J. Parker, and K. Hoyt
    Ultrasonics, vol. 94 , pp. 28 -36  (2019). View PDF
  22. Concentric layered Hermite scatterers
    J. P. Astheimer and K. J. Parker
    Phys Lett A, vol. 382, no. 21 , pp. 1379 -1382  (2018). View PDF
  23. H-scan analysis of thyroid lesions
    G. R. Ge, R. Laimas, J. Pinto, J. Guerrero, H. Chavez, C. Salazar, R. J. Lavarello, and K. J. Parker
    J Med Imaging, vol. 5, no. 1 , pp. 013505-1 -013505-9  (2018). View PDF
  24. Spatial angular compounding technique for H-scan ultrasound imaging
    M. Khairalseed, F. Xiong, J. Kim, R. F. Mattrey, K. J. Parker, and K. Hoyt
    Ultrasound Med Biol, vol. 44, no. 1 , pp. 267 -277  (2018). View PDF
  25. H-scan sensitivity to scattering size
    M. Khairalseed, K. Hoyt, J. Ormachea, A. Terrazas, and K. J. Parker
    J Med Imaging, vol. 4, no. 4 , pp. 043501-1 -043501-7  (2017). View PDF
  26. Hermite scatterers in an ultraviolet sky
    K. J. Parker
    Phys Lett A, vol. 381, no. 46 , pp. 3845 -3848  (2017). View PDF
  27. The H-Scan format for classification of ultrasound scattering
    K. J. Parker
    OMICS Journal of Radiology, vol. 5, no. 5 , p. 1000236  (2016). View Online
  28. Scattering and reflection identification in H-scan images
    K. J. Parker
    Physics in Medicine and Biology, vol. 61, no. 12 , pp. L20 -L28  (2016). View Online