The collected PA signal was first filtered using a 128th order finite impulse response (FIR) bandpass filter.
(4a g) were integrated using a 4th/5th order Runge-Kutta solver (MATLAB's ode45 function), with the obtained concentrations of acetate, propionate, PHB, PHV, PH2MV and oxygen subtracted from the respective measured values to give the residuals.
Here, Zernike moments are calculated using a 10-order parameter.
Data were reconstructed using a 2D ordered subset expectation maximization (OSEM2D) algorithm.
PET images were reconstructed using a 2D ordered subset expectation maximization (OSEM2D) algorithm, and were corrected for scatter and random events, dead time, and decay.
PET data were collected over a period of 20 min (one bed position), and the 3D sinograms were reconstructed using a 3D ordered subset expectation maximization followed by a maximum a posteriori algorithm (3D OSEM-MAP).
To compute these peaks, the velocity was low-pass filtered using a 6-order Butterworth filter (cut-off frequency = 50Hz).
In the position independent case when using a 0-order background model and ignoring reverse complements (see below), the sum decomposes into sums over the probabilities of bases at each position.
For each bed position, PET data were sampled into a 128 × 128 × 47 matrix with a voxel size of 4.7 × 4.7 × 3.27 mm and reconstructed using a 3D ordered subset expectation maximization algorithm (OSEM) with corrections for random, scatter, and attenuation incorporated into the iterative process.
