Download e-book for iPad: Advanced Image Acquisition, Processing Techniques, Applns, by D. Ventzas

By D. Ventzas

ISBN-10: 9535103423

ISBN-13: 9789535103424

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Extra resources for Advanced Image Acquisition, Processing Techniques, Applns,

Example text

For each section, section 2 presents the imaging protocol and animal groups for image acquisition; section 3 introduces the fat extraction method; section 4 describes the depot separation algorithm. In section 5, the automatic results is compared to manual reference for validataion. After that, the conclusion and acknowledgement is given in section 6 and section 7 respectively. 2. 1 Imaging sequence on micro MRI The experiments were performed on micro MRI scanner (70/16 Bruker PharmaScan, Germany).

1998) Si(S0,T2)=S0*exp(-Tei/T2) (1) with Tei=i*te and S0 is the pseudo-proton density, which is relative to the true proton density, T1 value and receiver coil response. 2 Fitting methods T2 value can be calculated by fitting the experimental data to above model in equation (1). To accomplish the fitting, a fitting method should be adopted. Here we have a comparison of the least square and weighted square method. A least square method (LS) is the common way of fitting the curve, which consists in minimizing the quadratic distance between the fitted curve and the curve represented by the raw data.

1-11. ; Tlibblin, G. (1984). Abdominal adipose tissue distribution, obesity and risk of cardiovascular disease and death: 13 y follow up of participants in the study of men born in 1913. 1401-1404. (2009). Automated separation of visceral and subcutaneous adiposity in in-vivo microcoputed tomographies of mice. 222-231. (2009). In vivo quantification of subcutaneous and visceral adiposity by micro-computed tomography in a small animal model. 34-41. V. (1974). The Influence of Obesity in Health. New England Journal of Medicine, 1974, Vol.

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Advanced Image Acquisition, Processing Techniques, Applns, by D. Ventzas

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