Scattering Signatures of Normal versus Abnormal Livers with Support Vector Machine Classification
| Autor: | Sedigheh S. Poul, Kevin J. Parker, Jihye Baek, Terri A. Swanson, Theresa Tuthill |
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| Rok vydání: | 2020 |
| Předmět: |
Male
Support Vector Machine Acoustics and Ultrasonics Biophysics Article 030218 nuclear medicine & medical imaging Rats Sprague-Dawley 03 medical and health sciences Speckle pattern 0302 clinical medicine Animals Radiology Nuclear Medicine and imaging Ultrasonography 030304 developmental biology 0303 health sciences Normal conditions Radiological and Ultrasound Technology Scattering Multiparametric Analysis business.industry Liver Diseases Matched filter Ultrasound Rats Support vector machine Liver Principal component analysis business Biomedical engineering |
| Zdroj: | Ultrasound Med Biol |
| ISSN: | 0301-5629 |
| DOI: | 10.1016/j.ultrasmedbio.2020.08.009 |
| Popis: | Fifty years of research on the nature of backscatter from tissues has resulted in a number of promising diagnostic parameters. We recently introduced two analyses tied directly to the biophysics of ultrasound scattering: the H-scan, based on a matched filter approach to distinguishing scattering transfer functions, and the Burr distribution for quantification of speckle patterns. Together, these analyses can produce at least five parameters that are directly linked to the mathematics of ultrasound in tissue. These have been measured in vivo in 35 rat livers under normal conditions and after exposure to compounds that induce inflammation, fibrosis, and steatosis in varying combinations. A classification technique, the support vector machine, is employed to determine clusters of the five parameters that are signatures of the different liver conditions. With the multiparametric measurement approach and determination of clusters, the different types of liver pathology can be discriminated with 94.6% accuracy. |
| Databáze: | OpenAIRE |
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