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In Section 3, we briefly review the PF algorithm and provide computational details for implementing the method in blind estimation.
Also, for implementing the method in [26], we used the region segmentation algorithm [40] instead of their reported one.
Finally, results of this method are presented and compared to other classification methods, and the considerations for implementing the method in hardware are briefly discussed.
It is important to quantify the precision of low-field MRI first, since this is prerequisite before implementing the method in clinical practice.
This chapter merely lists concepts more specific to certain issues, which have however proven valuable, and sometimes vital, in implementing the method in an operational context.
We also describe our experience implementing the method in a field trial of a clean water and handwashing intervention in Dhaka, Bangladesh, the first time the method has been used.
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Here, we selected the multi-kernel function and implemented the method in the R package BGLR.
We have successfully implemented the method in the code CFX-4.
We implement the method in [24] to determine skin samples by using Cb and Cr values directly.
For a fair comparison, we also implemented the method in [8] using the frequency-domain image registration algorithm [18] which is used in the proposed method.
We have implemented the method in three different languages: FORTRAN, IDL (Interactive Data Language) and MATLAB (Matrix Laboratory).1 The procedure for analysis is schematically depicted in Fig. 1.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com