Clusters of Ultrasound Scattering Parameters for the Classification of Steatotic and Normal Livers

Ultrasound in Medicine & Biology - Tập 47 - Trang 3014-3027 - 2021
Jihye Baek1, Sedigheh S. Poul2, Lokesh Basavarajappa3, Shreya Reddy3, Haowei Tai4, Kenneth Hoyt3,5, Kevin J. Parker1
1Department of Electrical and Computer Engineering, University of Rochester, Rochester, New York, USA
2Department of Mechanical Engineering, University of Rochester, Rochester, New York, USA
3Department of Bioengineering, University of Texas at Dallas, Richardson, Texas, USA
4Department of Electrical and Computer Engineering, University of Texas at Dallas, Richardson, Texas, USA
5Department of Radiology University of Texas Southwestern Medical Center, Dallas, Texas USA

Tài liệu tham khảo

Andrade, 2012, Classifier approaches for liver steatosis using ultrasound images, Proc Technol, 5, 763, 10.1016/j.protcy.2012.09.084 Baek, 2020, H-Scan, shear wave and bioluminescent assessment of the progression of pancreatic cancer metastases in the liver, Ultrasound Med Biol, 46, 3369, 10.1016/j.ultrasmedbio.2020.08.006 Baek, 2020, Scattering signatures of normal versus abnormal livers with support vector machine classification, Ultrasound Med Biol, 46, 3379, 10.1016/j.ultrasmedbio.2020.08.009 Bamber, 1979, Theoretical modelling of the acoustic scattering structure of human liver, Acoust Lett, 3, 114 Barry, 2014, Detection of steatosis through shear speed dispersion: A rat study Barry, 2015, Shear wave dispersion in lean versus steatotic rat livers, J Ultrasound Med, 34, 1123, 10.7863/ultra.34.6.1123 Bishop, 2006, 325 Burckhardt, 1978, Speckle in ultrasound B-mode scans, IEEE Trans Sonics Ultrason, 25, 1, 10.1109/T-SU.1978.30978 Burr, 1942, Cumulative frequency functions, Ann Math Stat, 13, 215, 10.1214/aoms/1177731607 Byra, 2018, Transfer learning with deep convolutional neural network for liver steatosis assessment in ultrasound images, Int J Comput Assist Radiol Surg, 13, 1895, 10.1007/s11548-018-1843-2 Campbell, 1984, Measurements of calf liver ultrasonic differential and total scattering cross sections, J Acoust Soc Am, 75, 603, 10.1121/1.390534 Chiappini, 2017, Metabolism dysregulation induces a specific lipid signature of nonalcoholic steatohepatitis in patients, Sci Rep, 7, 46658, 10.1038/srep46658 Chivers, 1975, A spectral approach to ultrasonic scattering from human tissue: Methods, objectives and backscattering measurements, Phys Med Biol, 20, 799, 10.1088/0031-9155/20/5/009 Cortes, 1995, Support-vector networks, Mach Learn, 20, 273, 10.1007/BF00994018 Freese, 1977, Ultrasonic backscatter from human liver tissue: Its dependence on frequency and protein/lipid composition, J Clin Ultrasound, 5, 307, 10.1002/jcu.1870050504 Ghoshal, 2012, Ex vivo study of quantitative ultrasound parameters in fatty rabbit livers, Ultrasound Med Biol, 38, 2238, 10.1016/j.ultrasmedbio.2012.08.010 Goceri, 2016, Quantification of liver fat: A comprehensive review, Comput Biol Med, 71, 174, 10.1016/j.compbiomed.2016.02.013 Gramiak, 1976, Diffraction characterization of tissue using ultrasound, Proc IEEE Int Ultrason Symp, 60 Howley, 2006, The effect of principal component analysis on machine learning accuracy with high-dimensional spectral data, Knowl Based Syst, 19, 363, 10.1016/j.knosys.2005.11.014 Insana, 1990, Describing small-scale structure in random media using pulse-echo ultrasound, J Acoust Soc Am, 87, 179, 10.1121/1.399283 Javanaud, 1989, The application of a fractal model to the scattering of ultrasound in biological media, J Acoust Soc Am, 86, 493, 10.1121/1.398228 Jayalakshmi, 2011, Statistical normalization and back propagation for classification, Int J Comput Theory Eng, 3, 1793 Jennings, 2018, NAFLD-NASH: An under-recognized epidemic, Curr Vasc Pharmacol, 16, 209, 10.2174/1570161115666170622074007 Jeon, 2021, Clinical feasibility of quantitative ultrasound imaging for suspected hepatic steatosis: Intra- and inter-examiner reliability and correlation with controlled attenuation parameter, Ultrasound Med Biol, 47, 438, 10.1016/j.ultrasmedbio.2020.11.009 Lin, 1987, Correlations of sound speed with tissue constituents in normal and diffuse liver disease, Ultrason Imaging, 9, 29, 10.1177/016173468700900103 Lizzi, 1983, Theoretical framework for spectrum analysis in ultrasonic tissue characterization, J Acoust Soc Am, 73, 1366, 10.1121/1.389241 Lu, 1999, Ultrasound backscatter and attenuation in human liver with diffuse disease, Ultrasound Med Biol, 25, 1047, 10.1016/S0301-5629(99)00055-1 Maklad, 1984, Attenuation of ultrasound in normal liver and diffuse liver disease in vivo, Ultrason Imaging, 6, 117, 10.1177/016173468400600201 Momenan, 1987, Application of cluster analysis and unsupervised learning to multivariate tissue characterization, Proc SPIE, 0768 Momenan, 1994, Image staining and differential diagnosis of ultrasound scans based on the Mahalanobis distance, IEEE Trans Med Imaging, 13, 37, 10.1109/42.276143 Munsterman, 2019, A novel automatic digital algorithm that accurately quantifies steatosis in NAFLD on histopathological whole-slide images, Cytometry B Clin Cytom, 96, 521, 10.1002/cyto.b.21790 Narayana, 1983, On the frequency dependence of attenuation in normal and fatty liver, IEEE Trans Son Ultrason, 30, 379, 10.1109/T-SU.1983.31444 Ozturk, 2018, Quantitative hepatic fat quantification in non-alcoholic fatty liver disease using ultrasound-based techniques: A review of literature and their diagnostic performance, Ultrasound Med Biol, 44, 2461, 10.1016/j.ultrasmedbio.2018.07.019 Parker, 2016, The H-scan format for classification of ultrasound scattering, J OMICS Radiol, 5 Parker, 2019, The first order statistics of backscatter from the fractal branching vasculature, J Acoust Soc Am, 146, 3318, 10.1121/1.5132934 Parker, 2019, Shapes and distributions of soft tissue scatterers, Phys Med Biol, 64, 10.1088/1361-6560/ab2485 Parker, 2020, Fine-tuning the H-scan for discriminating changes in tissue scatterers, Biomed Phys Eng Express, 6, 10.1088/2057-1976/ab9206 Parker, 1988, In-vivo measurements of ultrasound attenuation in normal or diseased liver, Ultrasound Med Biol, 14, 127, 10.1016/0301-5629(88)90180-9 Parker, 2018, The biomechanics of simple steatosis and steatohepatitis, Phys Med Biol, 63, 10.1088/1361-6560/aac09a Parker, 2019, The 3D spatial autocorrelation of the branching fractal vasculature, Acoustics, 1, 369, 10.3390/acoustics1020020 Parker, 2020, Burr, Lomax, Pareto, and logistic distributions from ultrasound speckle, Ultrason Imaging, 42, 203, 10.1177/0161734620930621 Parker, 2020, Speckle from branching vasculature: Dependence on number density, J Med Imaging, 7, 10.1117/1.JMI.7.2.027001 Pearson, 1901, On lines of closes fit to system of points in space, Dublin Philos Mag J Sci, 2, 559, 10.1080/14786440109462720 Peng, 2015, Vibrational signatures to discriminate liver steatosis grades, Analyst, 140, 1107, 10.1039/C4AN01679C Pirmoazen, 2020, Quantitative ultrasound approaches for diagnosis and monitoring hepatic steatosis in nonalcoholic fatty liver disease, Theranostics, 10, 4277, 10.7150/thno.40249 Schwen, 2016, Zonated quantification of steatosis in an entire mouse liver, Comput Biol Med, 73, 108, 10.1016/j.compbiomed.2016.04.004 Shapiro, 1992, Elastic waves scattering and radiation by fractal inhomogeneity of a medium, Geophys J Int, 110, 591, 10.1111/j.1365-246X.1992.tb02094.x Sharma, 2019, Attenuation of shear waves in normal and steatotic livers, Ultrasound Med Biol, 45, 895, 10.1016/j.ultrasmedbio.2018.12.002 Singh, 2014, An information fusion based method for liver classification using texture analysis of ultrasound images, Inform Fusion, 19, 91, 10.1016/j.inffus.2013.05.007 Taylor, 1986, Quantitative US attenuation in normal liver and in patients with diffuse liver disease: Importance of fat, Radiology, 160, 65, 10.1148/radiology.160.1.3520657 Vapnik, 1999, An overview of statistical learning theory, IEEE Trans Neural Networks, 10, 988, 10.1109/72.788640 Virmani, 2013, SVM-based characterization of liver ultrasound images using wavelet packet texture descriptors, J Digit Imaging, 26, 530, 10.1007/s10278-012-9537-8 Wernberg, 2020, Steatosis assessment with controlled attenuation parameter (CAP) in various diseases, 441 Zagzebski, 1993, Quantitative ultrasound imaging: In vivo results in normal liver, Ultrason Imaging, 15, 335, 10.1177/016173469301500405