Literature DB >> 9483775

Comparisons of the Rayleigh and K-distribution models using in vivo breast and liver tissue.

R C Molthen1, P M Shankar, J M Reid, F Forsberg, E J Halpern, C W Piccoli, B B Goldberg.   

Abstract

There is a strong interest in finding out which statistical model is the most appropriate for describing the envelope of the backscattered ultrasonic echoes from different types of tissues. The Rayleigh model is commonly employed, but this requires conditions, such as the presence of large number of randomly located scatterers with fairly uniform cross-sections, that are not always met. However, our research indicates that a model based on the K-distribution may provide a better fit to empirical data over a range of scattering conditions than the standard Rayleigh model. In this study, we looked at the K-distribution as a descriptor of the backscattered envelope of the breast and liver tissues (in vivo). By examining data from various tissue regions, a goodness-of-fit test (a least squares error method) was used to determine whether a Rayleigh or K-distribution model is more appropriate. From a large group of patients and volunteer scans (a total of 72 subjects), the fit between the K-distribution and the data is shown to have a much smaller error than the Rayleigh model.

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Year:  1998        PMID: 9483775     DOI: 10.1016/s0301-5629(97)00204-4

Source DB:  PubMed          Journal:  Ultrasound Med Biol        ISSN: 0301-5629            Impact factor:   2.998


  5 in total

1.  Utilizing spatial and spectral features of photoacoustic imaging for ovarian cancer detection and diagnosis.

Authors:  Hai Li; Patrick Kumavor; Umar Salman Alqasemi; Quing Zhu
Journal:  J Biomed Opt       Date:  2015-01       Impact factor: 3.170

2.  Generalized formulations producing a Burr distribution of speckle statistics.

Authors:  Kevin J Parker; Sedigheh S Poul
Journal:  J Med Imaging (Bellingham)       Date:  2022-04-01

3.  Conventional frequency ultrasonic biomarkers of cancer treatment response in vivo.

Authors:  Ali Sadeghi-Naini; Omar Falou; Hadi Tadayyon; Azza Al-Mahrouki; William Tran; Naum Papanicolau; Michael C Kolios; Gregory J Czarnota
Journal:  Transl Oncol       Date:  2013-06-01       Impact factor: 4.243

4.  Multifeature analysis of an ultrasound quantitative diagnostic index for classifying nonalcoholic fatty liver disease.

Authors:  Yin-Yin Liao; Kuen-Cheh Yang; Ming-Ju Lee; Kuo-Chin Huang; Jin-De Chen; Chih-Kuang Yeh
Journal:  Sci Rep       Date:  2016-10-13       Impact factor: 4.379

5.  Can acoustic structural quantification be used to characterize the ultrasound echotexture of the peripheral zone of breast lesions?

Authors:  Annika Bach; Clarissa Hameister; Torsten Slowinski; Ernst Michael Jung; Anke Thomas; Thomas Fischer
Journal:  Clin Hemorheol Microcirc       Date:  2019       Impact factor: 2.375

  5 in total

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